{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this recipe we'll perform several analyses that were originally published in [Lauber *et al.* (2009)](http://www.ncbi.nlm.nih.gov/pubmed/19502440) (commonly referred to as the *88 Soils* study). We'll focus on beta diversity analyses using scikit-bio, numpy, scipy, pandas, and matplotlib."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Background"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The *88 Soils* study analyzed bacterial communities in 88 soil samples taken from various locations in North and South America. The key finding of the study was that soil pH was significantly correlated with bacterial community composition. The study did not find strong correlation based on geographic location (e.g., latitude).\n",
    "\n",
    "In this notebok, we'll reproduce several of the beta diversity analyses that lead to these conclusions. Our analyses will center around two key pieces of data: an unweighted [UniFrac](http://aem.asm.org/content/71/12/8228.abstract) distance matrix (e.g., as produced by [QIIME](http://qiime.org/)) containing distances between soil microbiome samples, and metadata about each soil sample (e.g., pH, latitude, soil moisture deficit, etc.; this is typically referred to as a *mapping file* in QIIME-related studies).\n",
    "\n",
    "We won't include full details on how to generate a distance matrix from amplicon sequence data in this notebook, nor will we provide details about microbial ecology concepts and methodology (e.g., UniFrac, alpha/beta diversity, ordination techniques). For further reading, see the [Studying microbial diversity](http://readiab.org/book/latest/3/1) chapter of [*An Introduction to Applied Bioinformatics*](http://readiab.org/) and the tutorials on the [QIIME website](http://qiime.org/).\n",
    "\n",
    "The original sequence data and metadata were obtained from the QIIME database (study 103), which is currently being re-vamped as [Qiita](https://github.com/biocore/qiita), and processed as follows:\n",
    "\n",
    "1. The OTU table was generated using closed-reference OTU picking with QIIME 1.7.0 and [Greengenes](http://www.ncbi.nlm.nih.gov/pubmed/22134646) 13_8 97% OTUs. [uclust](http://bioinformatics.oxfordjournals.org/content/26/19/2460) was used as the underlying clustering method in `pick_closed_reference_otus.py` with the default 97% similarity.\n",
    "\n",
    "2. The unweighted UniFrac distance matrix was generated using [MacQIIME](http://www.wernerlab.org/software/macqiime) 1.8.0 with the following command:\n",
    "\n",
    "```\n",
    "beta_diversity_through_plots.py -i table.biom -m map.txt -o bdiv-even500 -t /macqiime/greengenes/gg_13_8_otus/trees/97_otus.tree -e 500 -aO 6\n",
    "```\n",
    "\n",
    "**Note:** The distance matrix and per-sample metadata used here are not identical to the data used in the *88 Soils* publication. The data used here were derived from the publication's original sequencing data, but different processing steps were used here (e.g., different software and/or versions, parameters, reference database, etc.). Thus, the results presented here do not exactly match the publication's results, but we expect to arrive at the same overall biological conclusions."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Getting started: loading the data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before performing our analyses, we need to load the unweighted UniFrac distance matrix and metadata mapping file. Both are stored on disk as tab-separated text. We'll load the distance matrix into an [skbio.DistanceMatrix](http://scikit-bio.org/docs/0.5.0/generated/generated/skbio.stats.distance.DistanceMatrix.html) object and the metadata into a [pandas.DataFrame](http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.html):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from skbio import DistanceMatrix\n",
    "\n",
    "unifrac_dm = DistanceMatrix.read('data/88-soils/dm.txt')\n",
    "df = pd.read_csv('data/88-soils/map.txt', sep='\\t', index_col=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's take a quick look at our distance matrix:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "85x85 distance matrix\n",
      "IDs:\n",
      "'LQ2.141729', 'IT2.141720', 'HI3.141676', 'MD2.141689', 'RT1.141654', ...\n",
      "Data:\n",
      "[[ 0.          0.72303965  0.75669608 ...,  0.75618327  0.71983899\n",
      "   0.80723333]\n",
      " [ 0.72303965  0.          0.67136327 ...,  0.71516397  0.6448562\n",
      "   0.7136385 ]\n",
      " [ 0.75669608  0.67136327  0.         ...,  0.67475805  0.75112105\n",
      "   0.67771871]\n",
      " ..., \n",
      " [ 0.75618327  0.71516397  0.67475805 ...,  0.          0.76704384\n",
      "   0.68621643]\n",
      " [ 0.71983899  0.6448562   0.75112105 ...,  0.76704384  0.          0.77375735]\n",
      " [ 0.80723333  0.7136385   0.67771871 ...,  0.68621643  0.77375735  0.        ]]\n"
     ]
    }
   ],
   "source": [
    "print(unifrac_dm)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notice that there are only 85 soil samples -- we're a few samples shy of the original 88 (actually, there are 89 total samples, but only 88 were used in the original paper). We have fewer samples than the published paper because our *even sampling depth* of 500 sequences per sample caused samples with too few sequences to be dropped.\n",
    "\n",
    "Now let's take a look at our metadata:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>BarcodeSequence</th>\n",
       "      <th>LinkerPrimerSequence</th>\n",
       "      <th>TARGET_SUBFRAGMENT</th>\n",
       "      <th>ASSIGNED_FROM_GEO</th>\n",
       "      <th>EXPERIMENT_CENTER</th>\n",
       "      <th>TITLE</th>\n",
       "      <th>RUN_PREFIX</th>\n",
       "      <th>TEXTURE</th>\n",
       "      <th>EXPERIMENT_ALIAS</th>\n",
       "      <th>DEPTH</th>\n",
       "      <th>...</th>\n",
       "      <th>PRIMER_READ_GROUP_TAG</th>\n",
       "      <th>PCR_PRIMERS</th>\n",
       "      <th>LIBRARY_CONSTRUCTION_PROTOCOL</th>\n",
       "      <th>ANNUAL_SEASON_PRECPT</th>\n",
       "      <th>LATITUDE</th>\n",
       "      <th>STUDY_REF</th>\n",
       "      <th>SOIL_MOISTURE_DEFICIT</th>\n",
       "      <th>REGION</th>\n",
       "      <th>STUDY_CENTER</th>\n",
       "      <th>Description</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>#SampleID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>IT2.141720</th>\n",
       "      <td>ACGTGCCGTAGA</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>loamy sand</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>750.0</td>\n",
       "      <td>47.183333</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-262</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HI3.141676</th>\n",
       "      <td>ACGCTATCTGGA</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>loamy sand</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>20.083333</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>108</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MD2.141689</th>\n",
       "      <td>ACTCGATTCGAT</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>sandy loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>150.0</td>\n",
       "      <td>34.900000</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>1054</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CA1.141704</th>\n",
       "      <td>ACACGAGCCACA</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>silt loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>400.0</td>\n",
       "      <td>36.050000</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>198</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PE5.141692</th>\n",
       "      <td>AGACTGCGTACT</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>clay loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>-12.633333</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-1900</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO1.141714</th>\n",
       "      <td>ACATGATCGTTC</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>sand</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>600.0</td>\n",
       "      <td>40.400000</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-309</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DF3.141696</th>\n",
       "      <td>ACCGCAGAGTCA</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>loamy sand</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>35.966667</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-328</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PE1.141715</th>\n",
       "      <td>ACTTGTAGCAGC</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>sandy loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>2100.0</td>\n",
       "      <td>-13.083333</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-2500</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SP2.141678</th>\n",
       "      <td>AGCGCTGATGTG</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>loamy sand</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>750.0</td>\n",
       "      <td>36.616667</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-402</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO3.141651</th>\n",
       "      <td>ACATTCAGCGCA</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>sandy loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>322.0</td>\n",
       "      <td>40.800000</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>231</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SA2.141687</th>\n",
       "      <td>AGATCGGCTCGA</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>sand</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>400.0</td>\n",
       "      <td>35.366667</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>198</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CM1.141723</th>\n",
       "      <td>ACATCACTTAGC</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>silty clay</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>850.0</td>\n",
       "      <td>33.300000</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>155</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LQ2.141729</th>\n",
       "      <td>ACTCACGGTATG</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>silty clay loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>3500.0</td>\n",
       "      <td>18.300000</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-2454</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SR2.141673</th>\n",
       "      <td>AGCTATCCACGA</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>sandy loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>500.0</td>\n",
       "      <td>34.683333</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>324</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CR1.141682</th>\n",
       "      <td>ACCACATACATC</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>850.0</td>\n",
       "      <td>33.933333</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>160</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VC1.141722</th>\n",
       "      <td>AGGTGTGATCGC</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>sandy loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>500.0</td>\n",
       "      <td>35.900000</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-175</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IE2.141655</th>\n",
       "      <td>ACGTCTGTAGCA</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>sandy loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>41.800000</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-610</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RT2.141710</th>\n",
       "      <td>AGAGTCCTGAGC</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>silty clay loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>840.0</td>\n",
       "      <td>31.466667</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>135</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BB1.141690</th>\n",
       "      <td>AAGAGATGTCGA</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>sandy loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>44.870000</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-680</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CC1.141721</th>\n",
       "      <td>ACACTAGATCCG</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>sand</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>720.0</td>\n",
       "      <td>45.400000</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-143</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TL2.141706</th>\n",
       "      <td>AGGACGCACTGT</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>silt loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>400.0</td>\n",
       "      <td>68.633333</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-212</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PE6.141700</th>\n",
       "      <td>AGAGAGCAAGTG</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>clay</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>4000.0</td>\n",
       "      <td>-12.650000</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-1600</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HI1.141693</th>\n",
       "      <td>ACGCGATACTGG</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>250.0</td>\n",
       "      <td>20.083333</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>858</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PE7.141734</th>\n",
       "      <td>AGAGCAAGAGCA</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>silty clay</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>4000.0</td>\n",
       "      <td>-12.650000</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-1600</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BF1.141647</th>\n",
       "      <td>AATCAGTCTCGT</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>41.583333</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-451</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TL1.141653</th>\n",
       "      <td>AGCTTGACAGCT</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>400.0</td>\n",
       "      <td>68.633333</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-212</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KP1.141713</th>\n",
       "      <td>ACTACAGCCTAT</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>silt loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>835.0</td>\n",
       "      <td>39.100000</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-81</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CL3.141664</th>\n",
       "      <td>ACAGTGCTTCAT</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>loamy sand</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>1250.0</td>\n",
       "      <td>34.616667</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-420</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SK3.141716</th>\n",
       "      <td>AGCAGTCGCGAT</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>467.0</td>\n",
       "      <td>53.600000</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-13</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SF1.141728</th>\n",
       "      <td>AGATGTTCTGCT</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>clay loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>250.0</td>\n",
       "      <td>35.383333</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>494</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LQ1.141701</th>\n",
       "      <td>ACTATTGTCACG</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>silt loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>18.300000</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-4112</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MD4.141660</th>\n",
       "      <td>ACTCTTCTAGAG</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>sandy loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>150.0</td>\n",
       "      <td>35.200000</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>1087</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IT1.141711</th>\n",
       "      <td>ACGTGAGAGAAT</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>sandy loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>750.0</td>\n",
       "      <td>47.166667</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-262</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BF2.141708</th>\n",
       "      <td>AATCGTGACTCG</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>41.583333</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-451</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SN3.141650</th>\n",
       "      <td>AGCGACTGTGCA</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>loamy sand</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>600.0</td>\n",
       "      <td>36.450000</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-252</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MP2.141695</th>\n",
       "      <td>ACTGTACGCGTA</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>sandy loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>2200.0</td>\n",
       "      <td>49.466667</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-1721</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AR3.141705</th>\n",
       "      <td>AACTGTGCGTAC</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>clay</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>1400.0</td>\n",
       "      <td>-27.733333</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-206</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JT1.141699</th>\n",
       "      <td>ACGTTAGCACAC</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>loamy sand</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>90.0</td>\n",
       "      <td>33.966667</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>1032</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BZ1.141724</th>\n",
       "      <td>ACACATGTCTAC</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>silt loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>260.0</td>\n",
       "      <td>64.800000</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>133</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HI4.141735</th>\n",
       "      <td>ACGCTCATGGAT</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>20.083333</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-392</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AR2.141703</th>\n",
       "      <td>AACTCGTCGATG</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>clay</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>1400.0</td>\n",
       "      <td>-27.733333</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-206</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SV2.141666</th>\n",
       "      <td>AGCTGACTAGTC</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>loamy sand</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>210.0</td>\n",
       "      <td>34.333333</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>444</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MD3.141707</th>\n",
       "      <td>ACTCGCACAGGA</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>loamy sand</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>150.0</td>\n",
       "      <td>34.900000</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>1054</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HF2.141686</th>\n",
       "      <td>ACGCAACTGCTA</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>sandy loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>42.500000</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-484</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HJ2.141717</th>\n",
       "      <td>ACGGTGAGTGTC</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>sandy loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>44.216667</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-1507</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SR3.141674</th>\n",
       "      <td>AGCTCCATACAG</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>500.0</td>\n",
       "      <td>34.683333</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>324</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CF3.141691</th>\n",
       "      <td>ACAGAGTCGGCT</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>silt loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>1300.0</td>\n",
       "      <td>42.116667</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-859</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SK2.141662</th>\n",
       "      <td>AGCAGCACTTGT</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>sandy loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>467.0</td>\n",
       "      <td>53.983333</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-13</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AR1.141727</th>\n",
       "      <td>AACGCACGCTAG</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>clay</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>1400.0</td>\n",
       "      <td>-27.733333</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-206</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BB2.141659</th>\n",
       "      <td>AAGCTGCAGTCG</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>sandy loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>44.866667</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-680</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GB3.141652</th>\n",
       "      <td>ACGACGTCTTAG</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>clay loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>400.0</td>\n",
       "      <td>39.316667</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-112</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GB2.141732</th>\n",
       "      <td>ACCTGTCTCTCT</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>400.0</td>\n",
       "      <td>39.316667</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-112</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PE3.141731</th>\n",
       "      <td>AGACCGTCAGAC</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>sandy loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>5500.0</td>\n",
       "      <td>-13.083333</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-3270</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MT1.141719</th>\n",
       "      <td>ACTGTCGAAGCT</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>sandy loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>450.0</td>\n",
       "      <td>46.800000</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>70</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SP1.141656</th>\n",
       "      <td>AGCGAGCTATCT</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>sandy loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>650.0</td>\n",
       "      <td>36.500000</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CL4.141667</th>\n",
       "      <td>ACAGTTGCGCGA</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>sandy loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>1250.0</td>\n",
       "      <td>34.616667</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-420</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KP4.141733</th>\n",
       "      <td>ACTAGCTCCATA</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>silt loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>835.0</td>\n",
       "      <td>39.100000</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-81</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VC2.141694</th>\n",
       "      <td>AGTACGCTCGAG</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>500.0</td>\n",
       "      <td>35.900000</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-175</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CL2.141671</th>\n",
       "      <td>ACAGCTAGCTTG</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>sandy loam</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>1250.0</td>\n",
       "      <td>34.616667</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-420</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SK1.141669</th>\n",
       "      <td>AGCACGAGCCTA</td>\n",
       "      <td>CATGCTGCCTCCCGTAGGAGT</td>\n",
       "      <td>V2</td>\n",
       "      <td>n</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing-Based Assessment of Soil pH as ...</td>\n",
       "      <td>FA6P1OK</td>\n",
       "      <td>loamy sand</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>0-0.05</td>\n",
       "      <td>...</td>\n",
       "      <td>V2</td>\n",
       "      <td>FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...</td>\n",
       "      <td>19502440</td>\n",
       "      <td>467.0</td>\n",
       "      <td>53.900000</td>\n",
       "      <td>lauber_88_soils</td>\n",
       "      <td>-13</td>\n",
       "      <td>0</td>\n",
       "      <td>CCME</td>\n",
       "      <td>Pyrosequencing_based_assessment_of_soil_pH_as_...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>89 rows × 58 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           BarcodeSequence   LinkerPrimerSequence TARGET_SUBFRAGMENT  \\\n",
       "#SampleID                                                              \n",
       "IT2.141720    ACGTGCCGTAGA  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "HI3.141676    ACGCTATCTGGA  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "MD2.141689    ACTCGATTCGAT  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "CA1.141704    ACACGAGCCACA  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "PE5.141692    AGACTGCGTACT  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "CO1.141714    ACATGATCGTTC  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "DF3.141696    ACCGCAGAGTCA  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "PE1.141715    ACTTGTAGCAGC  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "SP2.141678    AGCGCTGATGTG  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "CO3.141651    ACATTCAGCGCA  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "SA2.141687    AGATCGGCTCGA  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "CM1.141723    ACATCACTTAGC  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "LQ2.141729    ACTCACGGTATG  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "SR2.141673    AGCTATCCACGA  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "CR1.141682    ACCACATACATC  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "VC1.141722    AGGTGTGATCGC  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "IE2.141655    ACGTCTGTAGCA  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "RT2.141710    AGAGTCCTGAGC  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "BB1.141690    AAGAGATGTCGA  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "CC1.141721    ACACTAGATCCG  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "TL2.141706    AGGACGCACTGT  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "PE6.141700    AGAGAGCAAGTG  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "HI1.141693    ACGCGATACTGG  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "PE7.141734    AGAGCAAGAGCA  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "BF1.141647    AATCAGTCTCGT  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "TL1.141653    AGCTTGACAGCT  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "KP1.141713    ACTACAGCCTAT  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "CL3.141664    ACAGTGCTTCAT  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "SK3.141716    AGCAGTCGCGAT  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "SF1.141728    AGATGTTCTGCT  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "...                    ...                    ...                ...   \n",
       "LQ1.141701    ACTATTGTCACG  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "MD4.141660    ACTCTTCTAGAG  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "IT1.141711    ACGTGAGAGAAT  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "BF2.141708    AATCGTGACTCG  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "SN3.141650    AGCGACTGTGCA  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "MP2.141695    ACTGTACGCGTA  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "AR3.141705    AACTGTGCGTAC  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "JT1.141699    ACGTTAGCACAC  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "BZ1.141724    ACACATGTCTAC  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "HI4.141735    ACGCTCATGGAT  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "AR2.141703    AACTCGTCGATG  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "SV2.141666    AGCTGACTAGTC  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "MD3.141707    ACTCGCACAGGA  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "HF2.141686    ACGCAACTGCTA  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "HJ2.141717    ACGGTGAGTGTC  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "SR3.141674    AGCTCCATACAG  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "CF3.141691    ACAGAGTCGGCT  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "SK2.141662    AGCAGCACTTGT  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "AR1.141727    AACGCACGCTAG  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "BB2.141659    AAGCTGCAGTCG  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "GB3.141652    ACGACGTCTTAG  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "GB2.141732    ACCTGTCTCTCT  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "PE3.141731    AGACCGTCAGAC  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "MT1.141719    ACTGTCGAAGCT  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "SP1.141656    AGCGAGCTATCT  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "CL4.141667    ACAGTTGCGCGA  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "KP4.141733    ACTAGCTCCATA  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "VC2.141694    AGTACGCTCGAG  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "CL2.141671    ACAGCTAGCTTG  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "SK1.141669    AGCACGAGCCTA  CATGCTGCCTCCCGTAGGAGT                 V2   \n",
       "\n",
       "           ASSIGNED_FROM_GEO EXPERIMENT_CENTER  \\\n",
       "#SampleID                                        \n",
       "IT2.141720                 n              CCME   \n",
       "HI3.141676                 n              CCME   \n",
       "MD2.141689                 n              CCME   \n",
       "CA1.141704                 n              CCME   \n",
       "PE5.141692                 n              CCME   \n",
       "CO1.141714                 n              CCME   \n",
       "DF3.141696                 n              CCME   \n",
       "PE1.141715                 n              CCME   \n",
       "SP2.141678                 n              CCME   \n",
       "CO3.141651                 n              CCME   \n",
       "SA2.141687                 n              CCME   \n",
       "CM1.141723                 n              CCME   \n",
       "LQ2.141729                 n              CCME   \n",
       "SR2.141673                 n              CCME   \n",
       "CR1.141682                 n              CCME   \n",
       "VC1.141722                 n              CCME   \n",
       "IE2.141655                 n              CCME   \n",
       "RT2.141710                 n              CCME   \n",
       "BB1.141690                 n              CCME   \n",
       "CC1.141721                 n              CCME   \n",
       "TL2.141706                 n              CCME   \n",
       "PE6.141700                 n              CCME   \n",
       "HI1.141693                 n              CCME   \n",
       "PE7.141734                 n              CCME   \n",
       "BF1.141647                 n              CCME   \n",
       "TL1.141653                 n              CCME   \n",
       "KP1.141713                 n              CCME   \n",
       "CL3.141664                 n              CCME   \n",
       "SK3.141716                 n              CCME   \n",
       "SF1.141728                 n              CCME   \n",
       "...                      ...               ...   \n",
       "LQ1.141701                 n              CCME   \n",
       "MD4.141660                 n              CCME   \n",
       "IT1.141711                 n              CCME   \n",
       "BF2.141708                 n              CCME   \n",
       "SN3.141650                 n              CCME   \n",
       "MP2.141695                 n              CCME   \n",
       "AR3.141705                 n              CCME   \n",
       "JT1.141699                 n              CCME   \n",
       "BZ1.141724                 n              CCME   \n",
       "HI4.141735                 n              CCME   \n",
       "AR2.141703                 n              CCME   \n",
       "SV2.141666                 n              CCME   \n",
       "MD3.141707                 n              CCME   \n",
       "HF2.141686                 n              CCME   \n",
       "HJ2.141717                 n              CCME   \n",
       "SR3.141674                 n              CCME   \n",
       "CF3.141691                 n              CCME   \n",
       "SK2.141662                 n              CCME   \n",
       "AR1.141727                 n              CCME   \n",
       "BB2.141659                 n              CCME   \n",
       "GB3.141652                 n              CCME   \n",
       "GB2.141732                 n              CCME   \n",
       "PE3.141731                 n              CCME   \n",
       "MT1.141719                 n              CCME   \n",
       "SP1.141656                 n              CCME   \n",
       "CL4.141667                 n              CCME   \n",
       "KP4.141733                 n              CCME   \n",
       "VC2.141694                 n              CCME   \n",
       "CL2.141671                 n              CCME   \n",
       "SK1.141669                 n              CCME   \n",
       "\n",
       "                                                        TITLE RUN_PREFIX  \\\n",
       "#SampleID                                                                  \n",
       "IT2.141720  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "HI3.141676  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "MD2.141689  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "CA1.141704  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "PE5.141692  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "CO1.141714  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "DF3.141696  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "PE1.141715  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "SP2.141678  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "CO3.141651  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "SA2.141687  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "CM1.141723  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "LQ2.141729  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "SR2.141673  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "CR1.141682  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "VC1.141722  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "IE2.141655  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "RT2.141710  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "BB1.141690  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "CC1.141721  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "TL2.141706  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "PE6.141700  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "HI1.141693  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "PE7.141734  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "BF1.141647  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "TL1.141653  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "KP1.141713  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "CL3.141664  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "SK3.141716  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "SF1.141728  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "...                                                       ...        ...   \n",
       "LQ1.141701  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "MD4.141660  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "IT1.141711  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "BF2.141708  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "SN3.141650  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "MP2.141695  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "AR3.141705  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "JT1.141699  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "BZ1.141724  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "HI4.141735  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "AR2.141703  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "SV2.141666  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "MD3.141707  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "HF2.141686  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "HJ2.141717  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "SR3.141674  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "CF3.141691  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "SK2.141662  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "AR1.141727  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "BB2.141659  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "GB3.141652  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "GB2.141732  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "PE3.141731  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "MT1.141719  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "SP1.141656  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "CL4.141667  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "KP4.141733  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "VC2.141694  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "CL2.141671  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "SK1.141669  Pyrosequencing-Based Assessment of Soil pH as ...    FA6P1OK   \n",
       "\n",
       "                    TEXTURE EXPERIMENT_ALIAS   DEPTH  \\\n",
       "#SampleID                                              \n",
       "IT2.141720       loamy sand  lauber_88_soils  0-0.05   \n",
       "HI3.141676       loamy sand  lauber_88_soils  0-0.05   \n",
       "MD2.141689       sandy loam  lauber_88_soils  0-0.05   \n",
       "CA1.141704        silt loam  lauber_88_soils  0-0.05   \n",
       "PE5.141692        clay loam  lauber_88_soils  0-0.05   \n",
       "CO1.141714             sand  lauber_88_soils  0-0.05   \n",
       "DF3.141696       loamy sand  lauber_88_soils  0-0.05   \n",
       "PE1.141715       sandy loam  lauber_88_soils  0-0.05   \n",
       "SP2.141678       loamy sand  lauber_88_soils  0-0.05   \n",
       "CO3.141651       sandy loam  lauber_88_soils  0-0.05   \n",
       "SA2.141687             sand  lauber_88_soils  0-0.05   \n",
       "CM1.141723       silty clay  lauber_88_soils  0-0.05   \n",
       "LQ2.141729  silty clay loam  lauber_88_soils  0-0.05   \n",
       "SR2.141673       sandy loam  lauber_88_soils  0-0.05   \n",
       "CR1.141682             loam  lauber_88_soils  0-0.05   \n",
       "VC1.141722       sandy loam  lauber_88_soils  0-0.05   \n",
       "IE2.141655       sandy loam  lauber_88_soils  0-0.05   \n",
       "RT2.141710  silty clay loam  lauber_88_soils  0-0.05   \n",
       "BB1.141690       sandy loam  lauber_88_soils  0-0.05   \n",
       "CC1.141721             sand  lauber_88_soils  0-0.05   \n",
       "TL2.141706        silt loam  lauber_88_soils  0-0.05   \n",
       "PE6.141700             clay  lauber_88_soils  0-0.05   \n",
       "HI1.141693             loam  lauber_88_soils  0-0.05   \n",
       "PE7.141734       silty clay  lauber_88_soils  0-0.05   \n",
       "BF1.141647             loam  lauber_88_soils  0-0.05   \n",
       "TL1.141653             loam  lauber_88_soils  0-0.05   \n",
       "KP1.141713        silt loam  lauber_88_soils  0-0.05   \n",
       "CL3.141664       loamy sand  lauber_88_soils  0-0.05   \n",
       "SK3.141716             loam  lauber_88_soils  0-0.05   \n",
       "SF1.141728        clay loam  lauber_88_soils  0-0.05   \n",
       "...                     ...              ...     ...   \n",
       "LQ1.141701        silt loam  lauber_88_soils  0-0.05   \n",
       "MD4.141660       sandy loam  lauber_88_soils  0-0.05   \n",
       "IT1.141711       sandy loam  lauber_88_soils  0-0.05   \n",
       "BF2.141708             loam  lauber_88_soils  0-0.05   \n",
       "SN3.141650       loamy sand  lauber_88_soils  0-0.05   \n",
       "MP2.141695       sandy loam  lauber_88_soils  0-0.05   \n",
       "AR3.141705             clay  lauber_88_soils  0-0.05   \n",
       "JT1.141699       loamy sand  lauber_88_soils  0-0.05   \n",
       "BZ1.141724        silt loam  lauber_88_soils  0-0.05   \n",
       "HI4.141735             loam  lauber_88_soils  0-0.05   \n",
       "AR2.141703             clay  lauber_88_soils  0-0.05   \n",
       "SV2.141666       loamy sand  lauber_88_soils  0-0.05   \n",
       "MD3.141707       loamy sand  lauber_88_soils  0-0.05   \n",
       "HF2.141686       sandy loam  lauber_88_soils  0-0.05   \n",
       "HJ2.141717       sandy loam  lauber_88_soils  0-0.05   \n",
       "SR3.141674             loam  lauber_88_soils  0-0.05   \n",
       "CF3.141691        silt loam  lauber_88_soils  0-0.05   \n",
       "SK2.141662       sandy loam  lauber_88_soils  0-0.05   \n",
       "AR1.141727             clay  lauber_88_soils  0-0.05   \n",
       "BB2.141659       sandy loam  lauber_88_soils  0-0.05   \n",
       "GB3.141652        clay loam  lauber_88_soils  0-0.05   \n",
       "GB2.141732             loam  lauber_88_soils  0-0.05   \n",
       "PE3.141731       sandy loam  lauber_88_soils  0-0.05   \n",
       "MT1.141719       sandy loam  lauber_88_soils  0-0.05   \n",
       "SP1.141656       sandy loam  lauber_88_soils  0-0.05   \n",
       "CL4.141667       sandy loam  lauber_88_soils  0-0.05   \n",
       "KP4.141733        silt loam  lauber_88_soils  0-0.05   \n",
       "VC2.141694             loam  lauber_88_soils  0-0.05   \n",
       "CL2.141671       sandy loam  lauber_88_soils  0-0.05   \n",
       "SK1.141669       loamy sand  lauber_88_soils  0-0.05   \n",
       "\n",
       "                                  ...                          \\\n",
       "#SampleID                         ...                           \n",
       "IT2.141720                        ...                           \n",
       "HI3.141676                        ...                           \n",
       "MD2.141689                        ...                           \n",
       "CA1.141704                        ...                           \n",
       "PE5.141692                        ...                           \n",
       "CO1.141714                        ...                           \n",
       "DF3.141696                        ...                           \n",
       "PE1.141715                        ...                           \n",
       "SP2.141678                        ...                           \n",
       "CO3.141651                        ...                           \n",
       "SA2.141687                        ...                           \n",
       "CM1.141723                        ...                           \n",
       "LQ2.141729                        ...                           \n",
       "SR2.141673                        ...                           \n",
       "CR1.141682                        ...                           \n",
       "VC1.141722                        ...                           \n",
       "IE2.141655                        ...                           \n",
       "RT2.141710                        ...                           \n",
       "BB1.141690                        ...                           \n",
       "CC1.141721                        ...                           \n",
       "TL2.141706                        ...                           \n",
       "PE6.141700                        ...                           \n",
       "HI1.141693                        ...                           \n",
       "PE7.141734                        ...                           \n",
       "BF1.141647                        ...                           \n",
       "TL1.141653                        ...                           \n",
       "KP1.141713                        ...                           \n",
       "CL3.141664                        ...                           \n",
       "SK3.141716                        ...                           \n",
       "SF1.141728                        ...                           \n",
       "...                               ...                           \n",
       "LQ1.141701                        ...                           \n",
       "MD4.141660                        ...                           \n",
       "IT1.141711                        ...                           \n",
       "BF2.141708                        ...                           \n",
       "SN3.141650                        ...                           \n",
       "MP2.141695                        ...                           \n",
       "AR3.141705                        ...                           \n",
       "JT1.141699                        ...                           \n",
       "BZ1.141724                        ...                           \n",
       "HI4.141735                        ...                           \n",
       "AR2.141703                        ...                           \n",
       "SV2.141666                        ...                           \n",
       "MD3.141707                        ...                           \n",
       "HF2.141686                        ...                           \n",
       "HJ2.141717                        ...                           \n",
       "SR3.141674                        ...                           \n",
       "CF3.141691                        ...                           \n",
       "SK2.141662                        ...                           \n",
       "AR1.141727                        ...                           \n",
       "BB2.141659                        ...                           \n",
       "GB3.141652                        ...                           \n",
       "GB2.141732                        ...                           \n",
       "PE3.141731                        ...                           \n",
       "MT1.141719                        ...                           \n",
       "SP1.141656                        ...                           \n",
       "CL4.141667                        ...                           \n",
       "KP4.141733                        ...                           \n",
       "VC2.141694                        ...                           \n",
       "CL2.141671                        ...                           \n",
       "SK1.141669                        ...                           \n",
       "\n",
       "            PRIMER_READ_GROUP_TAG  \\\n",
       "#SampleID                           \n",
       "IT2.141720                     V2   \n",
       "HI3.141676                     V2   \n",
       "MD2.141689                     V2   \n",
       "CA1.141704                     V2   \n",
       "PE5.141692                     V2   \n",
       "CO1.141714                     V2   \n",
       "DF3.141696                     V2   \n",
       "PE1.141715                     V2   \n",
       "SP2.141678                     V2   \n",
       "CO3.141651                     V2   \n",
       "SA2.141687                     V2   \n",
       "CM1.141723                     V2   \n",
       "LQ2.141729                     V2   \n",
       "SR2.141673                     V2   \n",
       "CR1.141682                     V2   \n",
       "VC1.141722                     V2   \n",
       "IE2.141655                     V2   \n",
       "RT2.141710                     V2   \n",
       "BB1.141690                     V2   \n",
       "CC1.141721                     V2   \n",
       "TL2.141706                     V2   \n",
       "PE6.141700                     V2   \n",
       "HI1.141693                     V2   \n",
       "PE7.141734                     V2   \n",
       "BF1.141647                     V2   \n",
       "TL1.141653                     V2   \n",
       "KP1.141713                     V2   \n",
       "CL3.141664                     V2   \n",
       "SK3.141716                     V2   \n",
       "SF1.141728                     V2   \n",
       "...                           ...   \n",
       "LQ1.141701                     V2   \n",
       "MD4.141660                     V2   \n",
       "IT1.141711                     V2   \n",
       "BF2.141708                     V2   \n",
       "SN3.141650                     V2   \n",
       "MP2.141695                     V2   \n",
       "AR3.141705                     V2   \n",
       "JT1.141699                     V2   \n",
       "BZ1.141724                     V2   \n",
       "HI4.141735                     V2   \n",
       "AR2.141703                     V2   \n",
       "SV2.141666                     V2   \n",
       "MD3.141707                     V2   \n",
       "HF2.141686                     V2   \n",
       "HJ2.141717                     V2   \n",
       "SR3.141674                     V2   \n",
       "CF3.141691                     V2   \n",
       "SK2.141662                     V2   \n",
       "AR1.141727                     V2   \n",
       "BB2.141659                     V2   \n",
       "GB3.141652                     V2   \n",
       "GB2.141732                     V2   \n",
       "PE3.141731                     V2   \n",
       "MT1.141719                     V2   \n",
       "SP1.141656                     V2   \n",
       "CL4.141667                     V2   \n",
       "KP4.141733                     V2   \n",
       "VC2.141694                     V2   \n",
       "CL2.141671                     V2   \n",
       "SK1.141669                     V2   \n",
       "\n",
       "                                                  PCR_PRIMERS  \\\n",
       "#SampleID                                                       \n",
       "IT2.141720  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "HI3.141676  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "MD2.141689  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "CA1.141704  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "PE5.141692  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "CO1.141714  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "DF3.141696  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "PE1.141715  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "SP2.141678  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "CO3.141651  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "SA2.141687  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "CM1.141723  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "LQ2.141729  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "SR2.141673  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "CR1.141682  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "VC1.141722  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "IE2.141655  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "RT2.141710  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "BB1.141690  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "CC1.141721  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "TL2.141706  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "PE6.141700  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "HI1.141693  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "PE7.141734  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "BF1.141647  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "TL1.141653  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "KP1.141713  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "CL3.141664  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "SK3.141716  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "SF1.141728  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "...                                                       ...   \n",
       "LQ1.141701  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "MD4.141660  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "IT1.141711  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "BF2.141708  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "SN3.141650  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "MP2.141695  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "AR3.141705  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "JT1.141699  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "BZ1.141724  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "HI4.141735  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "AR2.141703  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "SV2.141666  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "MD3.141707  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "HF2.141686  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "HJ2.141717  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "SR3.141674  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "CF3.141691  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "SK2.141662  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "AR1.141727  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "BB2.141659  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "GB3.141652  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "GB2.141732  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "PE3.141731  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "MT1.141719  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "SP1.141656  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "CL4.141667  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "KP4.141733  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "VC2.141694  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "CL2.141671  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "SK1.141669  FWD:GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG;...   \n",
       "\n",
       "            LIBRARY_CONSTRUCTION_PROTOCOL ANNUAL_SEASON_PRECPT   LATITUDE  \\\n",
       "#SampleID                                                                   \n",
       "IT2.141720                       19502440                750.0  47.183333   \n",
       "HI3.141676                       19502440               1000.0  20.083333   \n",
       "MD2.141689                       19502440                150.0  34.900000   \n",
       "CA1.141704                       19502440                400.0  36.050000   \n",
       "PE5.141692                       19502440               5000.0 -12.633333   \n",
       "CO1.141714                       19502440                600.0  40.400000   \n",
       "DF3.141696                       19502440               1100.0  35.966667   \n",
       "PE1.141715                       19502440               2100.0 -13.083333   \n",
       "SP2.141678                       19502440                750.0  36.616667   \n",
       "CO3.141651                       19502440                322.0  40.800000   \n",
       "SA2.141687                       19502440                400.0  35.366667   \n",
       "CM1.141723                       19502440                850.0  33.300000   \n",
       "LQ2.141729                       19502440               3500.0  18.300000   \n",
       "SR2.141673                       19502440                500.0  34.683333   \n",
       "CR1.141682                       19502440                850.0  33.933333   \n",
       "VC1.141722                       19502440                500.0  35.900000   \n",
       "IE2.141655                       19502440               1200.0  41.800000   \n",
       "RT2.141710                       19502440                840.0  31.466667   \n",
       "BB1.141690                       19502440               1200.0  44.870000   \n",
       "CC1.141721                       19502440                720.0  45.400000   \n",
       "TL2.141706                       19502440                400.0  68.633333   \n",
       "PE6.141700                       19502440               4000.0 -12.650000   \n",
       "HI1.141693                       19502440                250.0  20.083333   \n",
       "PE7.141734                       19502440               4000.0 -12.650000   \n",
       "BF1.141647                       19502440               1000.0  41.583333   \n",
       "TL1.141653                       19502440                400.0  68.633333   \n",
       "KP1.141713                       19502440                835.0  39.100000   \n",
       "CL3.141664                       19502440               1250.0  34.616667   \n",
       "SK3.141716                       19502440                467.0  53.600000   \n",
       "SF1.141728                       19502440                250.0  35.383333   \n",
       "...                                   ...                  ...        ...   \n",
       "LQ1.141701                       19502440               5000.0  18.300000   \n",
       "MD4.141660                       19502440                150.0  35.200000   \n",
       "IT1.141711                       19502440                750.0  47.166667   \n",
       "BF2.141708                       19502440               1000.0  41.583333   \n",
       "SN3.141650                       19502440                600.0  36.450000   \n",
       "MP2.141695                       19502440               2200.0  49.466667   \n",
       "AR3.141705                       19502440               1400.0 -27.733333   \n",
       "JT1.141699                       19502440                 90.0  33.966667   \n",
       "BZ1.141724                       19502440                260.0  64.800000   \n",
       "HI4.141735                       19502440               1500.0  20.083333   \n",
       "AR2.141703                       19502440               1400.0 -27.733333   \n",
       "SV2.141666                       19502440                210.0  34.333333   \n",
       "MD3.141707                       19502440                150.0  34.900000   \n",
       "HF2.141686                       19502440               1100.0  42.500000   \n",
       "HJ2.141717                       19502440               2000.0  44.216667   \n",
       "SR3.141674                       19502440                500.0  34.683333   \n",
       "CF3.141691                       19502440               1300.0  42.116667   \n",
       "SK2.141662                       19502440                467.0  53.983333   \n",
       "AR1.141727                       19502440               1400.0 -27.733333   \n",
       "BB2.141659                       19502440               1200.0  44.866667   \n",
       "GB3.141652                       19502440                400.0  39.316667   \n",
       "GB2.141732                       19502440                400.0  39.316667   \n",
       "PE3.141731                       19502440               5500.0 -13.083333   \n",
       "MT1.141719                       19502440                450.0  46.800000   \n",
       "SP1.141656                       19502440                650.0  36.500000   \n",
       "CL4.141667                       19502440               1250.0  34.616667   \n",
       "KP4.141733                       19502440                835.0  39.100000   \n",
       "VC2.141694                       19502440                500.0  35.900000   \n",
       "CL2.141671                       19502440               1250.0  34.616667   \n",
       "SK1.141669                       19502440                467.0  53.900000   \n",
       "\n",
       "                  STUDY_REF  SOIL_MOISTURE_DEFICIT  REGION STUDY_CENTER  \\\n",
       "#SampleID                                                                 \n",
       "IT2.141720  lauber_88_soils                   -262       0         CCME   \n",
       "HI3.141676  lauber_88_soils                    108       0         CCME   \n",
       "MD2.141689  lauber_88_soils                   1054       0         CCME   \n",
       "CA1.141704  lauber_88_soils                    198       0         CCME   \n",
       "PE5.141692  lauber_88_soils                  -1900       0         CCME   \n",
       "CO1.141714  lauber_88_soils                   -309       0         CCME   \n",
       "DF3.141696  lauber_88_soils                   -328       0         CCME   \n",
       "PE1.141715  lauber_88_soils                  -2500       0         CCME   \n",
       "SP2.141678  lauber_88_soils                   -402       0         CCME   \n",
       "CO3.141651  lauber_88_soils                    231       0         CCME   \n",
       "SA2.141687  lauber_88_soils                    198       0         CCME   \n",
       "CM1.141723  lauber_88_soils                    155       0         CCME   \n",
       "LQ2.141729  lauber_88_soils                  -2454       0         CCME   \n",
       "SR2.141673  lauber_88_soils                    324       0         CCME   \n",
       "CR1.141682  lauber_88_soils                    160       0         CCME   \n",
       "VC1.141722  lauber_88_soils                   -175       0         CCME   \n",
       "IE2.141655  lauber_88_soils                   -610       0         CCME   \n",
       "RT2.141710  lauber_88_soils                    135       0         CCME   \n",
       "BB1.141690  lauber_88_soils                   -680       0         CCME   \n",
       "CC1.141721  lauber_88_soils                   -143       0         CCME   \n",
       "TL2.141706  lauber_88_soils                   -212       0         CCME   \n",
       "PE6.141700  lauber_88_soils                  -1600       0         CCME   \n",
       "HI1.141693  lauber_88_soils                    858       0         CCME   \n",
       "PE7.141734  lauber_88_soils                  -1600       0         CCME   \n",
       "BF1.141647  lauber_88_soils                   -451       0         CCME   \n",
       "TL1.141653  lauber_88_soils                   -212       0         CCME   \n",
       "KP1.141713  lauber_88_soils                    -81       0         CCME   \n",
       "CL3.141664  lauber_88_soils                   -420       0         CCME   \n",
       "SK3.141716  lauber_88_soils                    -13       0         CCME   \n",
       "SF1.141728  lauber_88_soils                    494       0         CCME   \n",
       "...                     ...                    ...     ...          ...   \n",
       "LQ1.141701  lauber_88_soils                  -4112       0         CCME   \n",
       "MD4.141660  lauber_88_soils                   1087       0         CCME   \n",
       "IT1.141711  lauber_88_soils                   -262       0         CCME   \n",
       "BF2.141708  lauber_88_soils                   -451       0         CCME   \n",
       "SN3.141650  lauber_88_soils                   -252       0         CCME   \n",
       "MP2.141695  lauber_88_soils                  -1721       0         CCME   \n",
       "AR3.141705  lauber_88_soils                   -206       0         CCME   \n",
       "JT1.141699  lauber_88_soils                   1032       0         CCME   \n",
       "BZ1.141724  lauber_88_soils                    133       0         CCME   \n",
       "HI4.141735  lauber_88_soils                   -392       0         CCME   \n",
       "AR2.141703  lauber_88_soils                   -206       0         CCME   \n",
       "SV2.141666  lauber_88_soils                    444       0         CCME   \n",
       "MD3.141707  lauber_88_soils                   1054       0         CCME   \n",
       "HF2.141686  lauber_88_soils                   -484       0         CCME   \n",
       "HJ2.141717  lauber_88_soils                  -1507       0         CCME   \n",
       "SR3.141674  lauber_88_soils                    324       0         CCME   \n",
       "CF3.141691  lauber_88_soils                   -859       0         CCME   \n",
       "SK2.141662  lauber_88_soils                    -13       0         CCME   \n",
       "AR1.141727  lauber_88_soils                   -206       0         CCME   \n",
       "BB2.141659  lauber_88_soils                   -680       0         CCME   \n",
       "GB3.141652  lauber_88_soils                   -112       0         CCME   \n",
       "GB2.141732  lauber_88_soils                   -112       0         CCME   \n",
       "PE3.141731  lauber_88_soils                  -3270       0         CCME   \n",
       "MT1.141719  lauber_88_soils                     70       0         CCME   \n",
       "SP1.141656  lauber_88_soils                     17       0         CCME   \n",
       "CL4.141667  lauber_88_soils                   -420       0         CCME   \n",
       "KP4.141733  lauber_88_soils                    -81       0         CCME   \n",
       "VC2.141694  lauber_88_soils                   -175       0         CCME   \n",
       "CL2.141671  lauber_88_soils                   -420       0         CCME   \n",
       "SK1.141669  lauber_88_soils                    -13       0         CCME   \n",
       "\n",
       "                                                  Description  \n",
       "#SampleID                                                      \n",
       "IT2.141720  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "HI3.141676  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "MD2.141689  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "CA1.141704  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "PE5.141692  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "CO1.141714  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "DF3.141696  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "PE1.141715  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "SP2.141678  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "CO3.141651  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "SA2.141687  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "CM1.141723  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "LQ2.141729  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "SR2.141673  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "CR1.141682  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "VC1.141722  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "IE2.141655  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "RT2.141710  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "BB1.141690  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "CC1.141721  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "TL2.141706  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "PE6.141700  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "HI1.141693  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "PE7.141734  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "BF1.141647  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "TL1.141653  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "KP1.141713  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "CL3.141664  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "SK3.141716  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "SF1.141728  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "...                                                       ...  \n",
       "LQ1.141701  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "MD4.141660  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "IT1.141711  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "BF2.141708  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "SN3.141650  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "MP2.141695  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "AR3.141705  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "JT1.141699  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "BZ1.141724  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "HI4.141735  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "AR2.141703  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "SV2.141666  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "MD3.141707  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "HF2.141686  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "HJ2.141717  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "SR3.141674  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "CF3.141691  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "SK2.141662  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "AR1.141727  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "BB2.141659  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "GB3.141652  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "GB2.141732  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "PE3.141731  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "MT1.141719  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "SP1.141656  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "CL4.141667  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "KP4.141733  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "VC2.141694  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "CL2.141671  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "SK1.141669  Pyrosequencing_based_assessment_of_soil_pH_as_...  \n",
       "\n",
       "[89 rows x 58 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notice that there are 89 samples in the metadata `DataFrame`, and that the order of sample IDs in the distance matrix and metadata are not the same. This is okay: scikit-bio generally allows metadata to be a *superset* of the IDs present in the distance matrix (or ordination results, or whatever else you're working with). In other words, extra sample IDs in the metadata are okay, and they don't have to be in the same order as they are in the distance matrix.\n",
    "\n",
    "**Note:** scikit-bio currently only allows the metadata to be a superset of the IDs in the distance matrix. There are plans to support other modes, e.g., intersecting the metadata and distance matrix, or ignoring distance matrix IDs that are not found in the mapping file. See [#756](https://github.com/biocore/scikit-bio/issues/756) to track progress on this."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualizing beta diversity with ordination techniques"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now that we have our data loaded, let's visually explore the beta diversity of the 85 soils samples in our distance matrix, in the context of our per-sample metadata.\n",
    "\n",
    "The authors presented NMDS ordination plots of the soil samples colored by pH and biome. scikit-bio doesn't have the NMDS ordination technique yet -- there's an open issue (see [#99](https://github.com/biocore/scikit-bio/issues/99)) to have this functionality added. However, we can produce similar results using principal coordinates analysis (PCoA):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "from skbio.stats.ordination import pcoa\n",
    "\n",
    "pcoa_results = pcoa(unifrac_dm)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot the PCoA results, coloring each soil sample (i.e., each point) with its latitude:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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xmYxSkZeitCDtvVElS2IhlTkzXbHAdua0D25/q35PN4duus0nFiKFeod6Dupa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\n4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      "text/plain": [
       "<matplotlib.figure.Figure at 0x113e6d780>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# display matplotlib figures within the notebook\n",
    "%matplotlib inline\n",
    "\n",
    "fig = pcoa_results.plot(df=df,\n",
    "                        column='LATITUDE',\n",
    "                        axis_labels=['PC 1', 'PC 2', 'PC 3'],\n",
    "                        title='Samples colored by latitude',\n",
    "                        cmap='Reds',\n",
    "                        s=35)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There isn't much of a gradient pattern in the plot; this confirms the findings of the paper.\n",
    "\n",
    "If we color the soil samples by their pH, we see a clear gradient pattern from left (basic) to right (acidic). This visually confirms the correlation between soil bacterial community composition and change in pH that was the key finding in the paper. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Fhw4dWnoYSSMJt+EkYIOUcptu+QTgJQAp5TdCiFwhRLGUcle4HbUqgQH1IXV1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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x114119278>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = pcoa_results.plot(df=df,\n",
    "                        column='PH',\n",
    "                        axis_labels=['PC 1', 'PC 2', 'PC 3'],\n",
    "                        title='Samples colored by pH',\n",
    "                        cmap='Reds',\n",
    "                        s=35)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The only other environmental variable that was found to have significant correlation with community composition was soil moisture deficit:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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ZZ/P73/++0f7Bq69oVmPHH388ffv25ZRTTuGWW24JRIJpKSsr45133uGBBx6guLiY8vJy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\nGGNiyoLHGGNMTP0fNxxIFGZJ+LkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x119525390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = pcoa_results.plot(df=df,\n",
    "                        column='SOIL_MOISTURE_DEFICIT',\n",
    "                        axis_labels=['PC 1', 'PC 2', 'PC 3'],\n",
    "                        title='Samples colored by soil moisture deficit',\n",
    "                        cmap='Reds',\n",
    "                        s=35)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We see a pattern that's somewhat similar to the pH plot above. As the paper points out, pH and soil moisture deficit are strongly correlated environmental variables, which we confirm here by computing Pearson's correlation coefficient $r$:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.65196220317643994"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from scipy.stats import pearsonr\n",
    "\n",
    "pearsonr(df['PH'], df['SOIL_MOISTURE_DEFICIT'])[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Note:** The ordination plotting functionalty available in sckit-bio creates basic plots, and is intended to provide a quick look at your results in the context of metadata. For more interactivity, customization, and to generate publication-quality figures, we recommend EMPeror ([paper](http://www.gigasciencejournal.com/content/2/1/16/) | [website](http://biocore.github.io/emperor/)).\n",
    "\n",
    "To write the ordination results to file so that they can be loaded in EMPeror, run:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'data/88-soils/pcoa_results.txt'"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pcoa_results.write('data/88-soils/pcoa_results.txt')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Comparing distance matrices with the Mantel test"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now that we've visually explored beta diversity in the context of latitude, pH, and soil moisture deficit, let's quantify the strength of the relationships between community composition and environmental variables. There are a variety of techniques that can accomplish this; the original paper used the [Mantel test](http://www.ncbi.nlm.nih.gov/pubmed/6018555) to compute the correlation between the unweighted UniFrac distance matrix and distance matrices derived from environmental variables. We will replicate those analyses here.\n",
    "\n",
    "Let's define a convenience function to compute a `DistanceMatrix` from a numeric environmental variable (stored as a column in a `DataFrame`). We'll use the Euclidean distance metric:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import scipy.spatial.distance\n",
    "\n",
    "def dm_from_env(df, column):\n",
    "    distances = scipy.spatial.distance.pdist(df[column].values[:, np.newaxis], metric='euclidean')\n",
    "    return DistanceMatrix(distances, ids=df.index)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's create three distance matrices from our metadata (pH, soil moisture deficit, and latitude):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "ph_dm = dm_from_env(df, 'PH')\n",
    "soil_mois_dm = dm_from_env(df, 'SOIL_MOISTURE_DEFICIT')\n",
    "latitude_dm = dm_from_env(df, 'LATITUDE')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can use the Mantel test in scikit-bio to compare the UniFrac distance matrix with each of the environmental distance matrices. We use Spearman correlation instead of Pearson correlation (the default) to match the original publication:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.77870091183431622, 0.001, 85)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from skbio.stats.distance import mantel\n",
    "\n",
    "mantel(unifrac_dm, ph_dm, method='spearman', strict=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We receive three values: the correlation coefficient (Spearman's $\\rho$), p-value, and number of samples that matched between the two distance matrices.\n",
    "\n",
    "Note that 85 samples were used in the test. The metadata has 89 samples but our UniFrac distance matrix only has 85 samples, so the Mantel test only considered samples that were in **both** distance matrices (controlled via `strict=False`). Just as scikit-bio doesn't require the metadata and distance matrix to be in the same order, the Mantel test reorders the samples in each distance matrix before comparing them. See the [scikit-bio mantel documentation](http://scikit-bio.org/docs/0.5.0/generated/generated/skbio.stats.distance.mantel.html) for more details.\n",
    "\n",
    "Let's run the Mantel test on the other two environmental distance matrices we created:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.42167110480728659, 0.001, 85)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mantel(unifrac_dm, soil_mois_dm, method='spearman', strict=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.22958919478208206, 0.001, 85)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mantel(unifrac_dm, latitude_dm, method='spearman', strict=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "pH has strong correlation ($\\rho$=0.7787) with soil microbial community composition, which agrees with the major points made in the original *88 Soils* publication. Soil moisture deficit has moderate correlation ($\\rho=0.4217$), while latitude has weak correlation ($\\rho=0.2296$). These findings are also in line with the original study results.\n",
    "\n",
    "**Note:** The p-value reported for UniFrac versus latitude differs from the p-value reported in the original publication ($P > 0.15$), which was computed using [PRIMER v6](http://www.primer-e.com/). We are actively investigating the discrepancy between p-values, as the paper did not find significant results, while our notebook finds significant results.\n",
    "\n",
    "Instead of running each Mantel test separately, scikit-bio provides a convenience function for running Mantel tests for all pairs of distance matrices:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>statistic</th>\n",
       "      <th>p-value</th>\n",
       "      <th>n</th>\n",
       "      <th>method</th>\n",
       "      <th>permutations</th>\n",
       "      <th>alternative</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dm1</th>\n",
       "      <th>dm2</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">UniFrac</th>\n",
       "      <th>pH</th>\n",
       "      <td>0.778701</td>\n",
       "      <td>0.001</td>\n",
       "      <td>85</td>\n",
       "      <td>spearman</td>\n",
       "      <td>999</td>\n",
       "      <td>two-sided</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Soil moisture deficit</th>\n",
       "      <td>0.421671</td>\n",
       "      <td>0.001</td>\n",
       "      <td>85</td>\n",
       "      <td>spearman</td>\n",
       "      <td>999</td>\n",
       "      <td>two-sided</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Latitude</th>\n",
       "      <td>0.229589</td>\n",
       "      <td>0.001</td>\n",
       "      <td>85</td>\n",
       "      <td>spearman</td>\n",
       "      <td>999</td>\n",
       "      <td>two-sided</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">pH</th>\n",
       "      <th>Soil moisture deficit</th>\n",
       "      <td>0.348139</td>\n",
       "      <td>0.001</td>\n",
       "      <td>89</td>\n",
       "      <td>spearman</td>\n",
       "      <td>999</td>\n",
       "      <td>two-sided</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Latitude</th>\n",
       "      <td>0.069542</td>\n",
       "      <td>0.037</td>\n",
       "      <td>89</td>\n",
       "      <td>spearman</td>\n",
       "      <td>999</td>\n",
       "      <td>two-sided</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Soil moisture deficit</th>\n",
       "      <th>Latitude</th>\n",
       "      <td>0.318524</td>\n",
       "      <td>0.001</td>\n",
       "      <td>89</td>\n",
       "      <td>spearman</td>\n",
       "      <td>999</td>\n",
       "      <td>two-sided</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                             statistic  p-value   n    method  \\\n",
       "dm1                   dm2                                                       \n",
       "UniFrac               pH                      0.778701    0.001  85  spearman   \n",
       "                      Soil moisture deficit   0.421671    0.001  85  spearman   \n",
       "                      Latitude                0.229589    0.001  85  spearman   \n",
       "pH                    Soil moisture deficit   0.348139    0.001  89  spearman   \n",
       "                      Latitude                0.069542    0.037  89  spearman   \n",
       "Soil moisture deficit Latitude                0.318524    0.001  89  spearman   \n",
       "\n",
       "                                             permutations alternative  \n",
       "dm1                   dm2                                              \n",
       "UniFrac               pH                              999   two-sided  \n",
       "                      Soil moisture deficit           999   two-sided  \n",
       "                      Latitude                        999   two-sided  \n",
       "pH                    Soil moisture deficit           999   two-sided  \n",
       "                      Latitude                        999   two-sided  \n",
       "Soil moisture deficit Latitude                        999   two-sided  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from skbio.stats.distance import pwmantel\n",
    "\n",
    "pwmantel([unifrac_dm, ph_dm, soil_mois_dm, latitude_dm],\n",
    "         labels=['UniFrac', 'pH', 'Soil moisture deficit', 'Latitude'],\n",
    "         method='spearman', strict=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We obtain the same results as above, but this time they are presented in a `DataFrame`.\n",
    "\n",
    "<font color=\"red\">**Warning:**</font> `pwmantel` doesn't correct the p-values for multiple comparisons (e.g., Bonferroni correction). It is the responsibility of the user to correct the p-values, though this feature may be added to scikit-bio in the future."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Linking evironmental variables to community structure"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Besides pH, soil moisture deficit, and latitude, there are many more environmental variables in our `DataFrame` that we haven't explored yet. Table 2 in the original paper has Mantel test results for several other evironmental variables, with a note stating that many more were analyzed but no significant correlations were found. The paper also states that multivariate correlations did not increase the strength of the correlation coefficients; thus, single environmental variables had higher correlation than combinations of two or more environmental variables.\n",
    "\n",
    "When there are a large number of environmental variables of potential interest, the `bioenv` method (originally called BIO-ENV, also known as BEST) can be helpful in finding subsets of variables that are maximally rank-correlated with the community distance matrix. See [Clarke & Ainsworth (1993)](http://www.int-res.com/articles/meps/92/m092p205.pdf) for the original method publication and the [scikit-bio bioenv documentation](http://scikit-bio.org/docs/0.5.0/generated/generated/skbio.stats.distance.bioenv.html) for more details.\n",
    "\n",
    "Let's define a list of 11 numeric environmental variables of potential interest. The names match the column names in the `DataFrame`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "env_vars = [\n",
    "    'TOT_ORG_CARB', 'SILT_CLAY', 'ELEVATION', 'SOIL_MOISTURE_DEFICIT',\n",
    "    'CARB_NITRO_RATIO', 'ANNUAL_SEASON_TEMP', 'ANNUAL_SEASON_PRECPT',\n",
    "    'PH', 'CMIN_RATE', 'LONGITUDE', 'LATITUDE'\n",
    "]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's run `bioenv` with our UniFrac distance matrix, metadata, and environmental variables we defined above:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>size</th>\n",
       "      <th>correlation</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>vars</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>PH</th>\n",
       "      <td>1</td>\n",
       "      <td>0.778703</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SOIL_MOISTURE_DEFICIT, PH</th>\n",
       "      <td>2</td>\n",
       "      <td>0.706704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SOIL_MOISTURE_DEFICIT, ANNUAL_SEASON_TEMP, PH</th>\n",
       "      <td>3</td>\n",
       "      <td>0.666790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SILT_CLAY, SOIL_MOISTURE_DEFICIT, ANNUAL_SEASON_TEMP, PH</th>\n",
       "      <td>4</td>\n",
       "      <td>0.629411</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SILT_CLAY, SOIL_MOISTURE_DEFICIT, CARB_NITRO_RATIO, ANNUAL_SEASON_TEMP, PH</th>\n",
       "      <td>5</td>\n",
       "      <td>0.594918</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SILT_CLAY, SOIL_MOISTURE_DEFICIT, CARB_NITRO_RATIO, ANNUAL_SEASON_TEMP, PH, LONGITUDE</th>\n",
       "      <td>6</td>\n",
       "      <td>0.575953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SILT_CLAY, SOIL_MOISTURE_DEFICIT, CARB_NITRO_RATIO, ANNUAL_SEASON_TEMP, ANNUAL_SEASON_PRECPT, PH, LONGITUDE</th>\n",
       "      <td>7</td>\n",
       "      <td>0.553162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TOT_ORG_CARB, SILT_CLAY, SOIL_MOISTURE_DEFICIT, CARB_NITRO_RATIO, ANNUAL_SEASON_TEMP, ANNUAL_SEASON_PRECPT, PH, LONGITUDE</th>\n",
       "      <td>8</td>\n",
       "      <td>0.535103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TOT_ORG_CARB, SILT_CLAY, SOIL_MOISTURE_DEFICIT, CARB_NITRO_RATIO, ANNUAL_SEASON_TEMP, ANNUAL_SEASON_PRECPT, PH, CMIN_RATE, LONGITUDE</th>\n",
       "      <td>9</td>\n",
       "      <td>0.509554</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TOT_ORG_CARB, SILT_CLAY, SOIL_MOISTURE_DEFICIT, CARB_NITRO_RATIO, ANNUAL_SEASON_TEMP, ANNUAL_SEASON_PRECPT, PH, CMIN_RATE, LONGITUDE, LATITUDE</th>\n",
       "      <td>10</td>\n",
       "      <td>0.482862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TOT_ORG_CARB, SILT_CLAY, ELEVATION, SOIL_MOISTURE_DEFICIT, CARB_NITRO_RATIO, ANNUAL_SEASON_TEMP, ANNUAL_SEASON_PRECPT, PH, CMIN_RATE, LONGITUDE, LATITUDE</th>\n",
       "      <td>11</td>\n",
       "      <td>0.458250</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    size  correlation\n",
       "vars                                                                 \n",
       "PH                                                     1     0.778703\n",
       "SOIL_MOISTURE_DEFICIT, PH                              2     0.706704\n",
       "SOIL_MOISTURE_DEFICIT, ANNUAL_SEASON_TEMP, PH          3     0.666790\n",
       "SILT_CLAY, SOIL_MOISTURE_DEFICIT, ANNUAL_SEASON...     4     0.629411\n",
       "SILT_CLAY, SOIL_MOISTURE_DEFICIT, CARB_NITRO_RA...     5     0.594918\n",
       "SILT_CLAY, SOIL_MOISTURE_DEFICIT, CARB_NITRO_RA...     6     0.575953\n",
       "SILT_CLAY, SOIL_MOISTURE_DEFICIT, CARB_NITRO_RA...     7     0.553162\n",
       "TOT_ORG_CARB, SILT_CLAY, SOIL_MOISTURE_DEFICIT,...     8     0.535103\n",
       "TOT_ORG_CARB, SILT_CLAY, SOIL_MOISTURE_DEFICIT,...     9     0.509554\n",
       "TOT_ORG_CARB, SILT_CLAY, SOIL_MOISTURE_DEFICIT,...    10     0.482862\n",
       "TOT_ORG_CARB, SILT_CLAY, ELEVATION, SOIL_MOISTU...    11     0.458250"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from skbio.stats.distance import bioenv\n",
    "\n",
    "res = bioenv(unifrac_dm, df, env_vars)\n",
    "res"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We see that the \"best\" subset of environmental variables is a subset of size 1, which only includes pH. This result confirms the findings of the paper: not only is pH strongly correlated with community composition, but including multiple environmental variables doesn't improve the correlation over using pH alone.\n",
    "\n",
    "Also note that pH and soil moisture deficit are the \"best\" subset for subset size 2. This intuitively makes sense because pH and soil moisture deficit are strongly correlated (we calculated this earlier).\n",
    "\n",
    "The results are stored as a `DataFrame`, so we can easily find the subset of environmental variables with the highest correlation. In this example, it's easy to find the largest correlation coefficient (it's pH), but the following technique can be handy if the results table is large:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'PH'"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res['correlation'].idxmax()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`bioenv` was not used in the original paper, but it can be a useful technique when there are a large number of environmental variables."
   ]
  }
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