{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Use Case 8: Outliers"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"When analyzing data, it's often crucial to identify outliers—extremely high or low data points that can greatly affect the overall conclusions. In this use case, we demonstrate how to utilize the Blacksheep package to find these outliers in the CPTAC (Clinical Proteomic Tumor Analysis Consortium) data. We'll focus on a specific phenomenon reported in the CPTAC breast cancer study. The study revealed that tumors classified as HER-2 enriched frequently showed exceptionally high abundance of ERBB2 phosphorylation, protein, and mRNA. We will validate this observation using an independent cohort of breast cancer tumors included in the cptac package."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Step 1: Importing packages and setting up the notebook\n",
"\n",
"First, we import the necessary Python packages for data analysis."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Next, we'll import the blacksheep and cptac packages to grab our proteomic and clinical data. The blacksheep package needs to be installed separately, which can be done via pip command: pip install blksheep. (Not blacksheep)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"import blacksheep\n",
"import cptac\n",
"\n",
"brca = cptac.Brca()\n",
"clinical = brca.get_clinical('mssm')\n",
"proteomics = brca.get_proteomics('umich')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Step 2: Binarize Data\n",
"\n",
"The Blacksheep package requires the annotations to be binary variables. The 'histologic_type' of our cptac tumors is divided into different types. To create a binary table of these histologic types, we use the binarize_annotations function from blacksheep. The resultant binary table is referred to as 'annotations'."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>histologic_type_Inflitrating Ductal Carcinoma</th>\n",
" <th>histologic_type_Inflitrating Lobular Carcinoma</th>\n",
" <th>histologic_type_Other (specify)</th>\n",
" <th>histologic_type_other, specify</th>\n",
" <th>histologic_type_IDC and DCIS</th>\n",
" <th>histologic_type_Infiltrating Ductal and Lobular Carcinoma</th>\n",
" <th>histologic_type_Mucinous Carcinoma</th>\n",
" <th>histologic_type_Infiltrating Ductal and Mucinous Carcinoma</th>\n",
" <th>histologic_type_invasive ductal carcinoma with extensive high-grade DCIS with comedonecrosis and features of papillary carcinoma</th>\n",
" <th>histologic_type_Mixed ductal and lobular features</th>\n",
" <th>histologic_type_Triple Negative</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Patient_ID</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>01BR001</th>\n",
" <td>Inflitrating Ductal Carcinoma</td>\n",
" <td>not-Inflitrating Lobular Carcinoma</td>\n",
" <td>not-Other (specify)</td>\n",
" <td>not-other, specify</td>\n",
" <td>not-IDC and DCIS</td>\n",
" <td>not-Infiltrating Ductal and Lobular Carcinoma</td>\n",
" <td>not-Mucinous Carcinoma</td>\n",
" <td>not-Infiltrating Ductal and Mucinous Carcinoma</td>\n",
" <td>not-invasive ductal carcinoma with extensive h...</td>\n",
" <td>not-Mixed ductal and lobular features</td>\n",
" <td>not-Triple Negative</td>\n",
" </tr>\n",
" <tr>\n",
" <th>01BR008</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>01BR009</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>01BR010</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>01BR015</th>\n",
" <td>Inflitrating Ductal Carcinoma</td>\n",
" <td>not-Inflitrating Lobular Carcinoma</td>\n",
" <td>not-Other (specify)</td>\n",
" <td>not-other, specify</td>\n",
" <td>not-IDC and DCIS</td>\n",
" <td>not-Infiltrating Ductal and Lobular Carcinoma</td>\n",
" <td>not-Mucinous Carcinoma</td>\n",
" <td>not-Infiltrating Ductal and Mucinous Carcinoma</td>\n",
" <td>not-invasive ductal carcinoma with extensive h...</td>\n",
" <td>not-Mixed ductal and lobular features</td>\n",
" <td>not-Triple Negative</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" histologic_type_Inflitrating Ductal Carcinoma \\\n",
"Patient_ID \n",
"01BR001 Inflitrating Ductal Carcinoma \n",
"01BR008 NaN \n",
"01BR009 NaN \n",
"01BR010 NaN \n",
"01BR015 Inflitrating Ductal Carcinoma \n",
"\n",
" histologic_type_Inflitrating Lobular Carcinoma \\\n",
"Patient_ID \n",
"01BR001 not-Inflitrating Lobular Carcinoma \n",
"01BR008 NaN \n",
"01BR009 NaN \n",
"01BR010 NaN \n",
"01BR015 not-Inflitrating Lobular Carcinoma \n",
"\n",
" histologic_type_Other (specify) histologic_type_other, specify \\\n",
"Patient_ID \n",
"01BR001 not-Other (specify) not-other, specify \n",
"01BR008 NaN NaN \n",
"01BR009 NaN NaN \n",
"01BR010 NaN NaN \n",
"01BR015 not-Other (specify) not-other, specify \n",
"\n",
" histologic_type_IDC and DCIS \\\n",
"Patient_ID \n",
"01BR001 not-IDC and DCIS \n",
"01BR008 NaN \n",
"01BR009 NaN \n",
"01BR010 NaN \n",
"01BR015 not-IDC and DCIS \n",
"\n",
" histologic_type_Infiltrating Ductal and Lobular Carcinoma \\\n",
"Patient_ID \n",
"01BR001 not-Infiltrating Ductal and Lobular Carcinoma \n",
"01BR008 NaN \n",
"01BR009 NaN \n",
"01BR010 NaN \n",
"01BR015 not-Infiltrating Ductal and Lobular Carcinoma \n",
"\n",
" histologic_type_Mucinous Carcinoma \\\n",
"Patient_ID \n",
"01BR001 not-Mucinous Carcinoma \n",
"01BR008 NaN \n",
"01BR009 NaN \n",
"01BR010 NaN \n",
"01BR015 not-Mucinous Carcinoma \n",
"\n",
" histologic_type_Infiltrating Ductal and Mucinous Carcinoma \\\n",
"Patient_ID \n",
"01BR001 not-Infiltrating Ductal and Mucinous Carcinoma \n",
"01BR008 NaN \n",
"01BR009 NaN \n",
"01BR010 NaN \n",
"01BR015 not-Infiltrating Ductal and Mucinous Carcinoma \n",
"\n",
" histologic_type_invasive ductal carcinoma with extensive high-grade DCIS with comedonecrosis and features of papillary carcinoma \\\n",
"Patient_ID \n",
"01BR001 not-invasive ductal carcinoma with extensive h... \n",
"01BR008 NaN \n",
"01BR009 NaN \n",
"01BR010 NaN \n",
"01BR015 not-invasive ductal carcinoma with extensive h... \n",
"\n",
" histologic_type_Mixed ductal and lobular features \\\n",
"Patient_ID \n",
"01BR001 not-Mixed ductal and lobular features \n",
"01BR008 NaN \n",
"01BR009 NaN \n",
"01BR010 NaN \n",
"01BR015 not-Mixed ductal and lobular features \n",
"\n",
" histologic_type_Triple Negative \n",
"Patient_ID \n",
"01BR001 not-Triple Negative \n",
"01BR008 NaN \n",
"01BR009 NaN \n",
"01BR010 NaN \n",
"01BR015 not-Triple Negative "
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"annotations = clinical[['histologic_type']].copy()\n",
"annotations = blacksheep.binarize_annotations(annotations)\n",
"annotations.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Step 3: Perform Outlier Analysis\n",
"\n",
"Now that our data frames are in the correct format, we perform the outlier analysis using the deva function in the blacksheep package. This function takes the proteomics data frame (transposed to meet the function's requirements) and the annotations data frame that includes binarized columns. The function returns two objects:\n",
"\n",
"1. A data object ('outliers') with a dataframe indicating whether a sample is an outlier for a specific protein.\n",
"2. A data object ('qvalues') with a dataframe showing the Q Values. These indicate if a gene shows an enrichment in outliers for a specific subset of tumors as defined in annotations."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"cptac warning: Your version of cptac (1.5.1) is out-of-date. Latest is 1.5.0. Please run 'pip install --upgrade cptac' to update it. (C:\\Users\\sabme\\anaconda3\\lib\\threading.py, line 910)\n"
]
}
],
"source": [
"outliers, qvalues = blacksheep.deva(proteomics.transpose(),\n",
" annotations,\n",
" up_or_down='up',\n",
" aggregate=False,\n",
" frac_filter=0.3)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Step 4: Inspect Results"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Because these two tables that are returned are quite complex, we will now look at each of these individually.\n",
"\n",
"The outliers table indicates whether each sample is an outlier for a particular gene. In this use case, we will focus on ERBB2. The first line below simplifies the index for each row by dropping the database id and leaving the gene name. We also only print off a portion of the table for brevity."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>01BR001_outliers</th>\n",
" <th>01BR008_outliers</th>\n",
" <th>01BR009_outliers</th>\n",
" <th>01BR010_outliers</th>\n",
" <th>01BR015_outliers</th>\n",
" <th>01BR017_outliers</th>\n",
" <th>01BR018_outliers</th>\n",
" <th>01BR020_outliers</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Name</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>ERBB2</th>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" 01BR001_outliers 01BR008_outliers 01BR009_outliers 01BR010_outliers \\\n",
"Name \n",
"ERBB2 0.0 0.0 0.0 0.0 \n",
"\n",
" 01BR015_outliers 01BR017_outliers 01BR018_outliers 01BR020_outliers \n",
"Name \n",
"ERBB2 0.0 1.0 0.0 0.0 "
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"outliers.df.index = outliers.df.index.droplevel('Database_ID')\n",
"erbb2_outliers = outliers.df[outliers.df.index.str.match('ERBB2')]\n",
"erbb2_outliers.iloc[:, :8]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"In the chart above you can see that most of the samples have 0, indiciating that the sample is not an outlier for ERBB2 protein abundance. 01BR017, however, has a 1, indicating that particular sample is an outlier.\n",
"\n",
"The Outliers table contains boolean columns for both outlier and notOutliers. The notOutliers columns are redundant so we will remove them."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"erbb2_outliers = erbb2_outliers.loc[:,~erbb2_outliers.columns.str.endswith('_notOutliers')]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can now complile a list of all the samples that were considered to be outliers."
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['01BR017_outliers', '05BR026_outliers', '06BR006_outliers', '09BR004_outliers', '09BR005_outliers', '11BR004_outliers', '11BR010_outliers', '11BR011_outliers', '11BR028_outliers', '11BR030_outliers', '11BR038_outliers', '11BR060_outliers', '11BR075_outliers', '18BR009_outliers', '21BR001_outliers', '22BR005_outliers']\n"
]
}
],
"source": [
"outlier_list = erbb2_outliers.columns[erbb2_outliers.isin([1.0]).all()].tolist()\n",
"print(outlier_list)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Step 5: Visualizing Outliers\n",
"To understand what this means, we will plot the proteomics data for the ERBB2 gene and label the outlier samples. Before we graph the result we will join the proteomics and clinical data, isolating the histologic type and ERBB2."
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"combined_data = brca.join_metadata_to_omics(metadata_name=\"clinical\",\n",
" metadata_source=\"mssm\",\n",
" metadata_cols=[\"histologic_type\"],\n",
" omics_name=\"proteomics\", \n",
" omics_source=\"umich\",\n",
" omics_genes=['ERBB2'])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We will now create the graph."
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 800x800 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(8, 8))\n",
"sns.set_palette('colorblind')\n",
"ax = sns.boxplot(data=combined_data, showfliers=False, y='ERBB2_umich_proteomics', color='lightgray')\n",
"left = False\n",
"# This for loop labels all the specific outlier data points.\n",
"for sample in outlier_list:\n",
" if left:\n",
" position = -0.08\n",
" left = False\n",
" else:\n",
" position = 0.01\n",
" left = True\n",
" sample = sample.split(\"_\")[0]\n",
" ax.annotate(sample, (position, combined_data.transpose()[sample].values[1]))\n",
"ax = sns.swarmplot(data=combined_data, y='ERBB2_umich_proteomics')\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"As you can see from this graph, the samples we labeled, which had a 1.0 in the outliers table were all located at the top of the graph, indicating they are very highly expressed."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Step 6: Looking at the Qvalue table\n",
"\n",
"Let's now take a look at the Qvalues table. Remember that the qvalues table indicates the probability that a gene shows an enrichment in outliers for categories defined in our annotation dataframe."
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th></th>\n",
" <th>fisherFDR_histologic_type_Inflitrating Ductal Carcinoma_not-Inflitrating Ductal Carcinoma</th>\n",
" <th>fisherFDR_histologic_type_Inflitrating Lobular Carcinoma_Inflitrating Lobular Carcinoma</th>\n",
" <th>fisherFDR_histologic_type_Other (specify)_Other (specify)</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Name</th>\n",
" <th>Database_ID</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>HSPB6</th>\n",
" <th>ENSP00000004982.3</th>\n",
" <td>NaN</td>\n",
" <td>0.019135</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SKAP2</th>\n",
" <th>ENSP00000005587.2</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.178671</td>\n",
" </tr>\n",
" <tr>\n",
" <th>UBR7</th>\n",
" <th>ENSP00000013070.6</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.178671</td>\n",
" </tr>\n",
" <tr>\n",
" <th>PTBP1</th>\n",
" <th>ENSP00000014112.5</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.178671</td>\n",
" </tr>\n",
" <tr>\n",
" <th>HEBP1</th>\n",
" <th>ENSP00000014930.4</th>\n",
" <td>NaN</td>\n",
" <td>0.062689</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" fisherFDR_histologic_type_Inflitrating Ductal Carcinoma_not-Inflitrating Ductal Carcinoma \\\n",
"Name Database_ID \n",
"HSPB6 ENSP00000004982.3 NaN \n",
"SKAP2 ENSP00000005587.2 NaN \n",
"UBR7 ENSP00000013070.6 NaN \n",
"PTBP1 ENSP00000014112.5 NaN \n",
"HEBP1 ENSP00000014930.4 NaN \n",
"\n",
" fisherFDR_histologic_type_Inflitrating Lobular Carcinoma_Inflitrating Lobular Carcinoma \\\n",
"Name Database_ID \n",
"HSPB6 ENSP00000004982.3 0.019135 \n",
"SKAP2 ENSP00000005587.2 NaN \n",
"UBR7 ENSP00000013070.6 NaN \n",
"PTBP1 ENSP00000014112.5 NaN \n",
"HEBP1 ENSP00000014930.4 0.062689 \n",
"\n",
" fisherFDR_histologic_type_Other (specify)_Other (specify) \n",
"Name Database_ID \n",
"HSPB6 ENSP00000004982.3 NaN \n",
"SKAP2 ENSP00000005587.2 0.178671 \n",
"UBR7 ENSP00000013070.6 0.178671 \n",
"PTBP1 ENSP00000014112.5 0.178671 \n",
"HEBP1 ENSP00000014930.4 NaN "
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"qvalues.df.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This table includes all the q-values. Before really analyzing the table we will want to remove any insignificant q-values. For our purposes we will remove any q-values that are greater than 0.05."
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"for col in qvalues.df.columns:\n",
" qvalues.df.loc[qvalues.df[col] > 0.05, col] = np.nan"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We will now isolate the ERBB2 gene."
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Name</th>\n",
" <th>fisherFDR_histologic_type_Inflitrating Ductal Carcinoma_not-Inflitrating Ductal Carcinoma</th>\n",
" <th>fisherFDR_histologic_type_Inflitrating Lobular Carcinoma_Inflitrating Lobular Carcinoma</th>\n",
" <th>fisherFDR_histologic_type_Other (specify)_Other (specify)</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
"Empty DataFrame\n",
"Columns: [Name, fisherFDR_histologic_type_Inflitrating Ductal Carcinoma_not-Inflitrating Ductal Carcinoma, fisherFDR_histologic_type_Inflitrating Lobular Carcinoma_Inflitrating Lobular Carcinoma, fisherFDR_histologic_type_Other (specify)_Other (specify)]\n",
"Index: []"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"qvalues.df.index = qvalues.df.index.droplevel('Database_ID')\n",
"qvalues = qvalues.df[qvalues.df.index.str.match('ERBB2')]\n",
"erbb2_qvalues = qvalues.reset_index()['Name'] == 'ERBB2'\n",
"qvalues = qvalues.reset_index()[erbb2_qvalues]\n",
"qvalues.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Here we see that none of the histologic types have a significant enrichment, which is exactly what is to be expected. To visualize this pattern, we will create a graph similiar to the one above, but with each of the categories in the histologic type category differentially colored. (Since there are many categories, some extra steps are taken to make the graph look less cluttered)."
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
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"text/plain": [
"<Figure size 800x800 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Setup\n",
"plt.figure(figsize=(8, 8))\n",
"sns.set_palette('colorblind')\n",
"cols = {'Inflitrating Ductal Carcinoma': 0, 'Inflitrating Lobular Carcinoma':1, 'Other (specify)':2, 'other, specify':3, 'IDC and DCIS':4, 'Infiltrating Ductal and Lobular Carcinoma':5, 'Mucinous Carcinoma':6, 'Infiltrating Ductal and Mucinous Carcinoma':7, 'invasive ductal carcinoma with extensive high-grade DCIS with comedonecrosis and features of papillary carcinoma':8, 'Mixed ductal and lobular features':9, 'Triple Negative':10}\n",
"\n",
"# Plotting\n",
"ax = sns.boxplot(data=combined_data, y='ERBB2_umich_proteomics', x='histologic_type', color='lightgray')\n",
"ax = sns.swarmplot(data=combined_data, y='ERBB2_umich_proteomics',x='histologic_type', hue='histologic_type')\n",
"\n",
"# Rotate x-labels for clarity\n",
"plt.xticks(rotation=45, ha=\"right\") # rotation by 45 degrees\n",
"\n",
"# Add annotations for outliers\n",
"for sample in outlier_list:\n",
" try:\n",
" sample = sample.split(\"_\")[0]\n",
" ax.annotate(sample, (cols[combined_data.transpose()[sample].values[0]], combined_data.transpose()[sample].values[1]))\n",
" except KeyError:\n",
" continue\n",
"\n",
"# Move the legend outside of the plot\n",
"ax.legend(loc='center left', bbox_to_anchor=(1, 0.5))\n",
"\n",
"plt.tight_layout() # Adjust layout to prevent any overlaps\n",
"plt.show()"
]
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"source": [
"## Additional Applications"
]
},
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"source": [
"We have just walked through one example of how you might use the Outlier Analysis. Using this same approach, you can run the outlier analysis on a number of different clinical attributes, cohorts, and omics data. For example, you may look for outliers within the transcriptomics of the Endometrial cancer type using the clinical attribute of histologic_type. You can also look at more than one clinical attribute at a time by appending more attributes to your annotations table, or you can look for downregulated omics by chaning the 'up_or_down' variable of the run_outliers function."
]
}
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