{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Tomancak et al Drosophila Data with GPy and Pandas\n", "\n", "#### presented at the EBI BioPreDyn Course 'The Systems Biology Modelling Cycle'\n", "\n", "### Neil Lawrence, 12th May 2014 with help from Marta Milo for the Bioconductor Portion\n", "\n", "#### Updated 18th March 2015 for latest GPy edition.\n", "\n", "### Introduction\n", "\n", "In this demonstration we are going to load pre-processed Affymetrix time series data. The data is pre-processed in R using bioconductor. The results are then loaded into a python for further analysis with a Gaussian process.\n", "\n", "The analysis we are going to do is to check whether any given set of replicates is 'valid'. In other words, were the replicates drawn from the same Gaussian process. To do this we will fit two Gaussian process models, one which assumes that the replicates are independent and one that assumes that they are drawn from the same process. We will evaluate the likelihood of each. The result could be used in a likelihood ratio test.\n", "\n", "### Preparing the Environment\n", "\n", "Firstly we load in the data set by downloading `cel` files if the analyzed files aren't already present on the disk. We load in `rmagic` if that data isn't present to do the preprocessing in the R PUMA package from bioconductor." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": false }, "outputs": [], "source": [ "import os\n", "import numpy as np\n", "import GPy\n", "import pods\n", "%matplotlib inline\n", "import matplotlib as plt\n", "plt.rcParams['figure.figsize'] = (10.0, 4.0)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Use Bioconductor for Processing\n", "\n", "Now we process the `cel` files using the PUMA package from bioconductor in R. This step can take a long time. The R code checks whether the preprocessed results are present and skips the processing of the `cel` files if they are. If you want to run the processing from scratch, delete any processed results stored in `datapath` and set the variable in the next box `process_data_in_R` to `True`." ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": false }, "outputs": [], "source": [ "# This downloads cel files if they are not present. \n", "# These cel files would be needed if you want to do \n", "# the full Bioconductor analysis below.\n", "process_data_in_R = False\n", "if process_data_in_R:\n", " %load_ext rmagic\n", " datapath = os.path.join(pods.datasets.data_path, 'fruitfly_tomancak')\n", " # download the original cel files and prepare to process!\n", " data_set = 'fruitfly_tomancak_cel_files'\n", " if not pods.datasets.data_available(data_set):\n", " data = pods.datasets.download_data(data_set)\n", "else:\n", " # download the puma-processed affymetrix data.\n", " data = pods.datasets.fruitfly_tomancak()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This portion of the code will do the PUMA analysis of the gene\n", "expression data in R. To run it needs to have the cel files\n", "from this fruitfly.org FTP server. The code above dowloads all the `cel` files and stores them in the path given by `datapath`. " ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "%%R -i datapath\n", "returnpath <- getwd()\n", "setwd(datapath)\n", "if(!file.exists(\"tomancak_exprs.csv\")) {\n", " source(\"http://www.bioconductor.org/biocLite.R\")\n", " biocLite(\"puma\")\n", " library(puma)\n", " print(\"Processing data with PUMA\")\n", " expfiles <- c(paste(\"embryo_tc_4_\", 1:12, \".CEL\", sep=\"\"), paste(\"embryo_tc_6_\", 1:12, \".CEL\", sep=\"\"), paste(\"embryo_tc_8_\", 1:12, \".CEL\", sep=\"\"))\n", " library(puma)\n", " drosophila_exp_set <- justmmgMOS(filenames=expfiles, celfile.path=datapath)\n", " pData(drosophila_exp_set) <- data.frame(\"time.h\" = rep(1:12, 3), row.names=rownames(pData(drosophila_exp_set))) \n", " write.reslts(drosophila_exp_set, file='tomancak')\n", "}\n", "else {\n", " print(\"Processed data found on disk.\")\n", "}\n", "setwd(returnpath)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Read Gene Expression Data into Pandas Dataframe\n", "\n", "Once the analysis is complete, the results are stored in the file `tomancak_exprs.csv`. To save you doing the full analysis, we can download a pre-processed version of this file using this command." ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false }, "outputs": [], "source": [ "data = pods.datasets.fruitfly_tomancak()\n", "X = data['X']\n", "Y = data['Y']" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The gene expression data is now loaded into the python environment. We have made use of `pandas` a python library for handling data structures. It provides us with a `DataFrame` object which gives some functionality similar to that of `R` for basic analysis.\n", "\n", "### Are these Replicates Really Valid?\n", "\n", "Next we are going to write a couple of python functions that allow us to do some simple processing of the gene expression data. The idea will be to see if the data is best modelled through a series of *identical* Gaussian processes, or through series of *independent* Gaussian processes. " ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": false }, "outputs": [], "source": [ "def fit_probe(id, independent=False):\n", " \"\"\"Fit a set of probe repeats as either independent or correlated.\"\"\"\n", " \n", " # set up the covariance function.\n", " lengthscale = 2.\n", " if independent:\n", " kern = GPy.kern.RBF(1,lengthscale=lengthscale)**GPy.kern.Coregionalize(1,3, rank=0)\n", " name = 'independent gp'\n", " else:\n", " kern = GPy.kern.RBF(1,lengthscale=lengthscale)**GPy.kern.Coregionalize(1,3, rank=1)\n", " kern.coregion.W[0] = 1.\n", " kern.coregion.W[1] = 1.\n", " kern.coregion.W[2] = 1.\n", " kern.coregion.W.constrain_fixed()\n", " name = 'joint gp'\n", "\n", " kern += GPy.kern.Bias(2)\n", " \n", " m = GPy.models.GPRegression(X, Y[id][:, None], kern)\n", " m.name = name\n", " m.optimize(messages=True)\n", " return m" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We'd like to display the model fits. The `GPy` software allows us to select which data to plot from the model. Below there's a function for plotting the data associated with each repliacte alongside the fit." ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": false }, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "from IPython.display import display\n", "\n", "def show_model_fit(m):\n", " display(m)\n", " fig, ax = plt.subplots(1, 3, sharex=False,sharey=True, figsize=(12, 3.5))\n", " symbols = ['x', 'x', 'x']\n", " replicate_str = 'replicate {}'\n", " #linecolors = [(1.,0.,0.), (0., 1., 0.), (0., 0., 1.)]\n", " mi, ma = np.inf, -np.inf\n", " for replicate in range(3):\n", " # Plot the result without noise (trying to estimate underlying gene expression)\n", " which_data_rows=np.nonzero(X[:,1]==replicate) \n", " data_symbol=symbols[replicate]\n", " pl = m.plot_f(ax=ax[replicate], fixed_inputs=[(1, replicate)], \n", " which_data_rows=which_data_rows,\n", " data_symbol=data_symbol,\n", " )\n", " ax[replicate].plot(m.X[which_data_rows, 0].flatten(), \n", " m.Y[which_data_rows].flatten(), \n", " data_symbol, c='k', mew=1.5,\n", " )\n", " ax[replicate].text(.98, .98, replicate_str.format(replicate), ha='right', va='top',\n", " transform=ax[replicate].transAxes)\n", " _mi, _ma = ax[replicate].get_ylim()\n", " if _mi < mi: mi = _mi\n", " if _ma > ma: ma = _ma\n", " for _ax in ax:\n", " _ax.set_ylim(mi, ma)\n", " ax[0].set_ylabel('gene expression [arbitrary]')\n", " ax[1].set_xlabel('time [hrs]')\n", " fig.text(0.5,1, m.name, ha='center', va='top', size=22, \n", " bbox=dict(facecolor='white', edgecolor='k', lw=.4, boxstyle='round'), clip_on=False)\n", " fig.tight_layout(rect=(0,0,1,1))\n", " #GPy.plotting.matplot_dep.base_plots.align_subplots(1, 3, xlim=ax[0].get_xlim(), ylim=ax[0].get_ylim())\n", " \n", "def fit_and_display(probe_id):\n", " mc = fit_probe(probe_id, independent=True)\n", " mi = fit_probe(probe_id, independent=False)\n", " show_model_fit(mc)\n", " show_model_fit(mi)\n", " return mc, mi" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now let's fit each of the two models to a given probe id. First we select a probe_id where the correspondence between the repeats is not very strong (even if it's there)." ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "

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v3o3W1lbs378feXl5aGxsxKFDhyY074yx5MLlCWMsllKtTOEAK44iNREEwLVYLOmsXbsW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\n3F0XLlzQqVOnSLIAAACAGIp0DRa2d/LkSZ0/f16XL19e/9r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YcM2i2Dza2NiInTt3xv/BOOdoamqiCoKLSKaeL5FJaEM6IYmjmDIziimEJI5iyswyooog\nY2wr5/x89Ov1AOyc884J11DgIosCBa6ZUWeIkMRRTJkZxRRCEkcxZWYZcdBwLLmK2jgxuSKEEEII\nIYSQhUjWPViMsa0ATs54ISGEEEIIIYQsAHIXudjOOXfKfA9CCCGEEEIIyQhyl2nfMN2T3/ve9+Jf\nb9myBVu2bJG5OYSQTPbqq6/i1VdfnfPrKaYQQsaimEIISaZEY4osRS4AgDFWDeBZzvmOKZ6nzaNk\nUaDNozOjDemEJI5iyswophCSOIopM5ttTJFzBosDaJfx/QnJGnRWCyEkmSimEEKSiWJKcsk2gzXj\njWlkiBAyAxptJoQkE8UUQkgypbRMOyGEEEIIIYQsRmlNsD7usqJ70AmvP5jOZhBCFojrPVYMjroR\nFsR0N4UQsgC099lhc/lpfwohZFbSmmAZjXpAqULvqB/Xuq3oG3FRx4gQMmd6vR5+kaGt34m2Xhus\nTh91jAghAABBlGb9Go1WC5snhGvdNnQOOBbcgHBjY+O4GMk5R2NjYxpbREj2mC5nSfsSQcYYDHoN\nDAY9QpICrX2RjpHTHUh30wghaeLzh3Ct2zqn16qUCpgMOmh1Ojh8Aq5129A16EQwJCS5lYSQbDFi\n9+IDy8icXqvVqGE06qFQqdFn9eNajxVDVg/EOSRsmaSxsRG7d+/GwYMHwTkH5xwHDx7E7t27Kcki\nZBqiKKFrwIHr3bYpr5H7HKxZUSkVyDHqAABDrgAG7F7kGzQoNhuhVKY9FySEyIxzjr4RFzwBEUaD\nft7vp1GroFGrIEkcHYMuKBlQlKeHOXf+700IyXyhsIiuQQeYUgW9Tjuv92KMQa/TAAC8YRG2Xjv0\nGiVKC4zQadXJaG5K7dy5E/X19Th27Fj8sWPHjqG+vh47d+5MY8sIyVwOdwADNi/0ei3U6qkHWTIq\nwRpLr40EMb8g4nqvHQatCqWFRmjVGdtkQsg8+AMhdA25odVpYDQkt7OiUDAYDZHBm1FPCEMOH8xG\nLYrNRigUVJqWkIVoxO7FqCsAo0EHxhh8/lDS3lutUkKt0oNzjs4hN1QKoDjfgDyTLmn3kBtjDEeP\nHgWAeJJVX1+Po0ePUsluQiaQJI7uQQdCEoPJOPMgbcZnKyqVEiaVHpLEYel3QqNSoKzACINek+6m\nEUKSZMjmgc0dSihozZdOowY0avgEEde6bcgxqFBamAMVzZITsiCIooSuQSdEJNYRmg/GPhm8GXYE\nMGTzojBPj8I8g6z3JYSkjtcfQs+wG1qdFnpNYn2FjE+wYhSKSKDknKNn1AsF82BpoRFG/fym/Akh\n6SOKEjoHnZCYAiZjakd+VUolTCY9wqKE1l47jDoVlhZRokVINvP6Q+gedkeW7yhS+39ZF10+aPeG\nMeq0oiBHh6J8Q8bOBsX2XMWWBQKfzGTRLBYhEUNWD2ze2Q8AZ02CFRMpihFJqnpGfVAyLyVahGQh\nfyCEjkE3DAYtNCnuCI2lUipgMuohSpRoEZLNRuxejLqDKZkJn442OkvuCgiw9thQmKNDsdmY1jZN\npqmpKZ5cxZYKApEka9euXdi1a1caW0dIekkSR+eAIzIAbJj9ADBLVwljxhjvHvEm5b18/iCUCmBZ\noTG+AZUQkrlsLj8G7T7kzNARWlFsnPSE9MkkK6aIkgS/P4gcvQplhTlUYIeQDMc5R8+QC0ER0xab\n8PlDuHmFOeUxJRQWEA6FUZyfeUsHGxsbsXPnzvhsFeccTU1NlFyRRS0YFtDR74RWp512sNXvD2D1\nisJJY8qCSLCASFDw+YPQqhiWFedCo1Ym7b0JIcnTP+qG2y8mtI8yHQlWjCBKCAaCyDdqsKTQRMtl\nCMlAgiiho98OlUYDlXL6z/10JVgxgVAYXBCwpMCYVcUwCFlM3N4gekc8MBp1M37uT5dgLZih2dhG\nU6Vag/Z+J7qHnFl/RgUhCwnnHB19dvhCUlYUqVEpFTAa9fCLwLVuG0bsyetoEULmLxgWcL3HDo1W\nN2NylQl0GjX0Bj2GnQG09tqSWtWQEDJ/ow4veq1emEz6eQ+qTrsHizGWO9MbcM5d82pBkjHGYDLq\nIEQ3rtPoMyHpJ4oSLP12qDUaaLOgIzSWSqmEyqiH0x+GzWVFWZERuSkuyEEIGc/tC6Jn2IMcU/ad\naaeLHkPTPeKBVsWwvCQXalV2xUVCFpr+UTc8AXFO+60mM1ORi04AlmmerwJQmJSWJJlKqYDKqIdP\nEHCt24YlZgMdLkpIGoQFEe19Duj0WijTWMxivmIb1wdsAQw7/CgvyaFz+QhJg8hBn76sTK7GMhp0\nkCSO1j4HcvUqLC3KpXP5CEmD7kEnQhKSWsdhpt7BCc75oameZIwdTlpLZKJWqaBWqTDqCmLU5cfy\nIhMVwiAkRYJhAZY+B4zG+U+3ZwqDXgPOOSwDLhi1SiwrokIYhKTKqMOLUVcw5cc6yEWhYMgx6hEW\nRFzrsaEkAwthELJQcc7R0e8AVyih1SR3wHTaXkEsuWKMPcUYq5zq+Wyg02mg0+nQNexB16ATAu3P\nIkRW/kAI7X1OmEyZew7MXDHGYDLoIEKJ6z122p9FSAoM2TywecLxg30XEpVKCZNRD5s3jOvdVtqf\nRYjMJImjvc8OplJBI8NqlESHXS8CaGCMXWSMPZbICxhjGxhjexhj++bevOQzGnTgCiXaeu0YtnvS\n3RxCFiSvP3LGVbYv4ZmJSqmAyaSH0y/gWrcVHn8w3U0iZEEaHHXD5RcW/AqUWCGM7hEPugYcMw4G\nNzY2Ymw1aM45Ghsb5W4mIVktklzZoFTPXH10rhJKsDjnpznnOwBsBfAgY0xijP3zZLNaYzzJOT8D\nIJ8xtn7+TU0epSJSHcwdkHCtywq3jzpFhCSLxx9E99DCT67G0mrUMBj06Bv1oaPfjrAgprtJhCwY\nA6NuuINSvDjEYmA06MCVKrT22jFknXwwuLGxEbt378bBgwfBOQfnHAcPHsTu3bspySJkCrHkSqWZ\n/oyr+UpoTowxthXAXgDbADQD2AigAMDp6NcTr38AwAUA4Jw/nazGJptGHZkW7Lf5oHH4qJIPIfPk\n8QfRM+SBaRElV2MZ9FpIEkdbrwMFOVqUFBgX3PJIQlKpf9QNb1Ca9gDhhUqpUMBk1MMTEuDosmJp\nsQk5Bm38+Z07d6K+vh7Hjh2LP3bs2DHU19dj586d6WgyIRlNkjhae2zQzHCAcDIkuujwUQDPcc4P\njH2QMfbUFNdvjD6/HsC2TE6yAMCgi3aK+hwwU1l3QubE6w8t6uQqRqFgMJkinSJ7tw1Lqaw7IXMy\nuIiTq7Fig8F9Vh+0YwaDGWM4evQoAMSTrPr6ehw9epT6MIRMEJu5SkVyBSS+B+tTnPPzEx/knJ+e\n5jWjnPMWAGCM7ZlL41JJoWAwGfXwhjmuddvg8gbS3SRCsoY/EELXkHvRJ1djadQqGI169Nv8sPTR\nskFCZmPI6oE7KC765Goso14LhUqDtj4HBkfd4/ZeEUKmxnlqlgWOlegM1nnG2EVElgcCAOecf2ea\n660AOqJfOwBsAnBm4kU/PPIP8a833/U5bL7r7gSbI5/YSNGALYBRhx/lS2jZICHTCYTCSSto8dab\nv8dbb74+59dnYkwx6mmGnJDZGLF74UxSQYuxMSUcnv0gR6bFlNhgsE8Q8HG3Ff945Hv45588g/r6\negCfzGTRLBYhEZHkyg6VWpOU5GpsTBHCwpTXsURGQKJ7qsbi0QIWU11fBeABzvnTjLHHAbRzzn81\n4RrePZLZpY0licMXCCDPoEEZdYoIuUEoLKKtz44ckzzntqwoNoJzntB/vGyIKWFBQCgURlmBEXkm\nWjZIyEQ2lx8jrgAMOu3MF8+Szx/CzSvMCyamvHr+ZTzy9fvx54/W4dmf/BM0aiUOHjyIY8eO4ezZ\ns9i1a1e6m0hI2lmipdjlqBbo9wewekXhpDEloQTrhhcxtj62/G+aa/YBsAHYONlsV6YHrrHCgoBQ\nMNopyqFOESEAIIgSWnvsMBp1sg0+LLQEK8YfCEHBOFaU5EKjTjzoNzY2YufOnfG/b845mpqaqCNF\nFgSHJ4BBm0+2c64WWoIFRJKsuz+/DV5/EPlGDUoLjHj55ZcpJhACoHvQiTBnspxzBUyfYCU0VxY9\nz+plxlgTY+xlACdneg3n/ATn/MwMSwmzgloV2Usx7Aqgrc+OYGjqKUFCFoPYAX0Gg3zJ1UKm12mg\n0WjQ3u9E77ATkjTzQBeVZCYLmccfRL/VuyAPEZbTlq07oFAokGPUIygC13rsuPMz96S7WYSkXe+w\nEyEJsiVXM0n0rnUAngSwH5HS7Ntka1EG02k14JzDMuiCUavEsqIcKFO0WY6QTME5h6XfDo1WC4WC\nkqu5YozBZNQhLIi41mNDSb4ehXlTL7WkksxkoQoEw+ge8iyqs/PkoFIqYTLqMeoKYtTpw/LinAV/\nMDMhkxmyeeAP87SenZdwWsc5v8wYA+e8mTG2X85GZTLGGEwGHQRRwvUeOwrztCgxm9LdLEJSprPf\nAaVanbJKPAudSqWESaWHzRuG1WnFsmITjPob959QSWayEIUFEZYBp2z7OBcjXTSp6hr2QK9RYllx\nDsVrsmjYXX44vGEYJvkcTaVE/8cZYqXWo3ur8uVrUnZQKRUwmfRwByRc67bC6aGy7mTh6x12QlIo\nZdksutjpNGroDXr0jvrQ0W9HaA4VzwjJJqIowdLngMlIM1dyMBp04AolWnvtVNadLApuXxCDdn/a\nkysg8QSrFMAlAIcA1ER/J4is7TQY9BhyRPZnBYLhdDeJkHEaGxvHfbByzue0Zycy5Z6+9cyLhSF2\n1k2/A73DToiiBADxPVexZYGx5YKxPVmEZBPOOToGHNDqtTQDKyOlQhEt685xrccGm8uf7iYRIotA\nMIzeEQ9MxszYx5lognUekb1XT0b//KA8zclesU3rnUNudA046FBRkhGSVRjB4Q7A4Q3ToZ8polAw\n5Bj1CHMlrvfYMWTzoLGxMZ5cHT16FEePHo0nWU1NTeluMiGz0jXohFKthlJBS9dSQa1SwWjQw+YJ\n4Xq3FW5fMN1NIiRpBFFCx4Azo2bDEx2KfhnAuejXNFQ6BcYYjAZd/FDRHL0KZYVUCIOkTzIKI3j9\nIfTbvMjJoMC1WMSWInuCAqpu/RROnvk1Hrj/y/ER/6NHj2LXrl1Ukplklf5RNwTOoKWlximn1agB\njRr9Vj+Udh/Ki3Og1dCqBJK9JInD0meHwZBZfZTZFLk4Hfs6th+LTC520npYEHG9x46CHC1KCoy0\nDIKk3HwLI4TCIrqG3FTdK800ahU0ahXuuPMetPbaUVpgQG70/DFKrkg2GXV44faLMOipul06GfSR\nqsgdgy5oVQzLimd3Jh8hmaJzwAF1BlY1njbBiiZSDwHYxhh7aMxTGwCckbNhC4FKpYTJpIc3LOBa\ntw2FuToUm43pbhYhCZEkDku/I2PWMxPES84O2gMYsvuwrNBEHVWSNdy+IEZcQZjorKuMMG7VTb8D\nJq0KS6niIMkiPUNOcIUS6gz8mZ1pBqsZQAuAJwAcHvO4TbYWLUBqlQpqlQqugABrtxVL8g0w59KM\nAJHfxMIIwCczWTPNYln67dDqaAN6JoqdbdMz6oVS4aVlPiTjBcMCeoc9MNFseMaJ7fkUJQmtvXbk\nGtQoK8zJuBkBQsYasXsREHjG7g2f6RN5P+f8acaYA5HDhmM4gO/I16yFKbbMZ9QdxIjTjyVmA/JM\nNJJH5NPU1DSuMELMsWPHpt270z3kBFOqaCQzwxn0WlrmQzKeKEqw9DthpNnwjBarOBgSRFzrtsFs\n0qCkwESJFsk4Lk8AVncQxgyeDZ+p92SJ/n4RwIXor4vRX2SOdFoN9Hodhp0BtPbYZK3mM98S3ckq\n8U3SY9euXTh79mx8tiq2J+vs2bNTJlfDdg+CApVjzxaxZT4KlQbt/U50DTqpiinJGLFy7Hoqx541\nYtsb/CJwrceGYbuHjoIgGSMYFtA76s3o5AqYIcHinJ+J/n46+vXlMV+TedJpNdDpdei3+tHaa4PP\nH0rq+8+3RHeySnyT9Nq1a9e4js10hRFcngBs7lDGTrmTqUWK6+gAhQqtfQ50DzkhRM/QIiRdeoZd\nUKhUVI7bpPUtAAAgAElEQVQ9C6mUSpiMergDEq712GB1+tLdJLLIRQ4nd2ZF4a2EhqijxS4OA7Aw\nxqoBPME5/5WsLVtEYpvUu0c8UCsZlidpP8V8S3Qno8Q3yR7BsIA+qzejzpEgsxfbTyGIkf0UeUYN\nSpO4zKexsRE7d+6MJ+2cczQ1NVE1Q3KD2Gy4Tkuz4dkstr3B7g1j1GlFCe0jJ2kQnw03aNPdlIQk\nGvW+wzlfGfsDY+wiAEqwksxo0IFzDsuAEwaNEkuLc6BWzX0/xXxLdM/39SR7xEaFaAP6wqFSRvZT\nBAUR13tsMJvmf1xEbFZ77J6+WBGV6ZadksXH5QnA7g7BkOHLeEjiYmdojbqDGHX6sSR6XAQhqdAz\nlF2z4YkmWBOrBlIVQZkwFjlDS5I4WvscMOlUWFZEhxUT+WTbqBCZHZVKCZUqelxEjw3FeXoU5hnm\n9F40q00SQbPhC9vE4yKWF5nilU0JkcOw3YOgmF2z4YmcgwUADsZYEyJl27cDcMz0xoyxw5zzQ4yx\nfZzzE/Nv6uIycZlPvlGDJYWmWY0+z6dEdzJeT7ID7ZFYHGLHRdi9YVidViwpMM66iinNapOZxCoG\nUnK18MWSqq5hD1UxJbLJ1tnwmVLBGkRKsncCGI0+1hx9bCb7GGNfw/jy7mSWVEoFVEY9fMLsR5/n\nWqI7Wa8nmY/2SCw+sWU+Q44Ahh00+kySZ2zFQLJ4jD2sOFevQllh4qtuaE8nmU6sYmA2FLWYiCVS\nepMx1jZ2D1ZCb8zYnumqDTLGePeIdzZvSQAEQmFwQcDSYhNMCXyIzTd4UfBbuFyeAPptvowudbqi\n2AjOeUJTIxRT5sbrC0CvUWJZcc6M555NNatNs1gEiJyfJ3AGtSozB2x8/hBuXmGmmCIjQZQQ8AdR\nmKdFidk07bW0p5NMRxQlXO+1Z/RsuN8fwOoVhZPGlEQTrOMAagGcA8AAcM75tAcNM8b2IXKO1gbO\n+dOTPE+Bax58/iA0SmB5Se68CmGQxSkYFtCeBaVOKcFKDVGS4PcHYZ5hKTJ1iMhUhu0eOH1iRh/x\nQAlW6oTCAsKhMJYWGacshEEDNmQ6bb02qDSajN6+kIwE64EJD/FEz8JijD0F4Bzn/PyExylwzZMk\ncfj8gRk7RYSMFRsVMhp0Gf8zQwlWaoXCAsLhMJYWGJE7xf4smtUmE2XDbDhACVY6+PwhqBQc5SWT\n788am2QBtKeTRGT6bHjMdAlWQi3nnJ8e+2fG2Prpro/OXtmiSZgVQDWA8xOv++GRf4h/vfmuz2Hz\nXXcn0hwSFTlY9JP9WdN1igiJie2RyMQPsLfe/D3eevP1Ob+eYsr8xM67GbAHMOL0Y8WSG2fIJyZS\n0x1cTRa+TN8jMTamhMPirF9PMWV+DHoNJImjvd9Bg8EkIZm+N3xsTBHCwpTXJTqDtQeRYhUckSWC\nVZzzVdNcvxXARc65MzqD9QvO+bsTrqGRoSTz+UPQKDktGyRTypZRoRiawUqf2Ax5gUmLJYXT76Ug\ni1M2zYYDNIOVbmFBQCgYxrJiE3IMWloiSG6QLbPhMfOewUIkuXoSwH4ApwFsm+5izvl5xtie6H+O\n0YnJFZFHbKSorc+BwtyZN5iSxSXTR4VIZonNkHtCAhxdVpSX5MCgp2qDJGJsxUDqCJNExI6K6Lf5\noHP68cHlP1Cl4gUgWcvGM302fLYS7mlxzi8zxsA5b2aM7U/g+oT2aKWSKEpwekPw+kMIhEWEQiKC\nYQGCKAGMQcEAgEGlVMCgU0GvUUGvUyNHr4ZWkx2d0linyOUPw+mxYkVpHrTq7Gg7kU+2niOR6YIh\nAU5vEL6AgGBYRCgciSmSxMEYA2ORJXQalTISU7RqGLQq5Bg0WXN4eGzZYPeIBwatEsuLc6FQUId6\nsesZovPzko1zDm8gDJc3iEBIRDAsIhgSEAqLAGNgiMQThYJBr1FG4olOBYNODaNOnTWJrkGnhShJ\nqF57J06e+TUeuP/L8bYfPXqUkqsskqzCR6IowZIFhbdmI9GeN4sdOhzdX5UvX5PmzusPod/qxaDV\ng4FRLwZsHthdATg8QTjcAbj9ISSwInJSBp0ahbk6FObpUZSnx7LiHCwrzsHyYhOKzUYoM6zDodWo\nwbkK7f1OFBg1KC3KSXeTSJoEgmH0jXphWkCBKxUkicPmDmBg1INBWySmDNq8cHgCcHqCcHiC8Aen\nXn89HcaAPJMWhbl6FObqsaTAEI0nkbiSa9RkXGfJaNBBEERc77FhWZEJOUY662ixGrJ6EBR5RlcM\nzERhQcSQzYcBqyf6y4tRhy/SR/EE4fQEIwO+c6BWKVCQE+mjFObqUVZkisYTE5YWmTJukFipUMBk\n1OOOO7fA0u+I7/ekPZ3ZZefOnaivr48XKQE+Wea5c+fOhN6Dcw5Lvx16w8L6TEloDxYAMMaqANgR\nWSr4S855y7xuPI+1zYIooW/EjY4BJzoGnOjsd6JryAmXNzTDPYEcgwY5Bg10GhW0aiW0GlU8OeKc\ngwMQBAn+oABfMAx/UIDLG5o26GnVSlQvzcfKcjNWLTfjpvIClJgTOww4FUJhAWI4jBVLcukDcZER\nRAnXe+xZOyqUqj1Y3kAYXbF4Ev29d8QdGTmehkrJkGfSwahTR+OJEhq1EooxSyU4B4JhMRJPAgJ8\ngfCMgz3mHB1WLTdjZbkZK5eZcVO5GQZd5vzf9QWC0KsUWF5Cs1mLjcMdwJDDD0MWHiacqj1YnHNY\nnf5P+ijR30fsXkgzdLn0WhXyjFrotKpPYsqYPdUS55AkjkBIgC8Q6ad4/eFpB3sYA5YX52Dl8kgf\nZVW5GZVl+RkzMCxJHH5/AMX5ehTmZU7fiSRmvpUgOwcc4AolVMrsqx0w5z1YjLGvcc5/BQCc847o\nw09O9ryc7O4APu6yRn/Z0DHgnDTh0aqVKC00oqzQhLJCI0oLTSjK0yPfpEV+jg65c1yWwzmH2xeC\n1RWAzeXHsM2H3hE3+kbc6B1xw+YK4GqXFVe7rPHXlBYYsW5lMdbVlOC2miLkpDEz16hVgFqFjkE3\nzEY1zWYtEpxzWPrsWbNZNFUkiaNn2B2JJ91WXO+2YcA6eScq16hBWWFkBLi0wIjSQiMKcvTIM2mR\nn6Od87IcQZTgcAdgdQVgdfoxaPOgd9iNvhEPekfcsLsD+OPVAfzx6gCAyNLfVcvNWFdTjHUrS3BT\neQHUqvQtzTLotBBECdd6bFge3bBOFj5/IIQBmzejD/5Mh2BIQGuvHR932/BxlxWtPXa4fTcO+CoY\nsKTAiLJoP6W00IgSswHmHB3yTVrkmXTQTlLKPBH+oAC72w+rM4BRpw99I554H2XQ6kXPsBs9w278\n7nI3AMCoU2NNdRFurynBupXFWFqUvup+CgWD0aiHzROCwxNERWnejIeek4VhcNQNgTNoszC5msm0\nM1iMsTYAzyJSOXAydZzzlXO68RQjQ5xzDFg9eL99NJ5UDdl9N1xXWmBEZVkeqsryULU0D5WleSjM\n06clQLi8QbT12tEa/fVxlw2+QDj+vIIBt1QW4c5by3DnmqUozk/fCE1sNquijPZmLXSWPntkj0QW\nB65kzGCFBQmtPTZ82DGKa902XOu2wTvm/ycQWV6zYknuJzGlLA8rluTCmIaiDpEY6EVrrx1tPXZc\n77Whvc8BaczQt0GnRu3qJfj0mqVYf9MS6NK4/MfnD0KvUaC8JDfjljWS5AkLIlp77cgxZe8MQ7Jm\nsNy+ID6wjOJqbNC33wFxwtRUjkGDqrK8eEypLMvH0iJTWgZGQmERnYNOtPbY0dZrx7VuGwZt47+v\nskIj7lyzFHfeuhSrlpvTNjMtSRw+XwClBQaYcymRz3TzqQRpc/kx4grAoMveAbo5HzQcPWB42gnt\nuRazGBu4HO4A3msfwXvtw3ivbQSjTv+4a3UaFW5aYcbNKwpxc0UhVpWbYcyg5TITiaIES78DV9pH\n8F7bMD7uskIQP/lrrFmWjy3rV+Cz65Yjz5T6HyzOOby+AIpydSg2G1N+fyK/3mEngiKLzF5msbkk\nWJxzdA+58V77MK60DeOjjlEEQuOX+hXl6XFzRSFurijA6hWFqCjNzegRU18gjA87RvFe+wiutA6j\nd8Qdf06jUmDD6lJs2bACG25akpbvQxBFBAMhVCzJgV5HlQYXGkniaO2xQZ8l5dinMtcEKxQW8XGX\nNfL/r20Yln7HuCW+CgZUlOVF+yiRmFKcn54B30QN272Rfldb5HsaO+NWkKvDXeuWY8v6Fagqy0tL\n+/yBEDQKjvIleVlTEGgxmmuRC48/iJ5hL0zG7F5hM+cES06MMf73P3sbV9qG0TXoGvdcrkGDtTXF\nWFNZhNUVBahYkpvV/8G8/hAuXRvCOx/1o+X6ULyzp1QwbFi9BJ/fUIFNN5em/HsMBENQgNN0/AIz\nYvfC4QtDp83+ju5sE6y/eeY1XGkfhsMdHPdceUkO1lYX45ZoUlWUxlnkZBiwevDOh/1456MBXOu2\nxR/PNWjwudvLce/GirR0jDy+AMwGWoa8kHDO0d5nh1KtyfrPibkkWI8efhlXO0cREj7ZlqBSKnDz\nigKsqS7CzRWFuKncDH0W728WRQkfd9nw9kf9eOejfow6PhnkrizLw5b15diyfgVyU1zYRhAlBAJB\nWoac4WZbpj0YFmDpcy6IwlsZm2Bt3PfvACIjsLdWFWFdTTFuX1mCitK8BbtxOhgWcfHqAH7X0o13\nW4fjy34K8/TY+akqbNtUifwUzmrFDhNdWmhEnim7RxJIZDZ40J49h/TNZLYJViymmHN08T2Qt68s\nRsECXmpidfrx+ys9ePVyN3qGP5nZuqWiELs3V+PTa5amtGMcCguQhDAqy/LpwPMFoHPAAYkpsuZw\n8unMJcGKxZSqsrx4TLmlsjCty3LlxDlHa68dr17uxhvv9cLjjyynVqsU+Oy65fjC5mrULDOntE1e\nXwA5ehWWFuVk9KwgmVm2F96aKGMTrO//+x9x+8oSrF5RAM0cN3ZmM7s7gNev9ODlP3aif9QDIDIy\ndte6Zfjq51ahojR1I9C+QBAGdaQqGAWw7OTxB9E97EFOlm5AF8RI9c7IrzAEUcLn71g+q87QT359\nBetWlqC8ZPF9EEdK3TrwyqVuvNrSHa8qZs7RYdedVdi9uRqmFO0po30UC0PfiAv+MIdWk32zM5xz\nhAQpHk8CQQFefwhf+HTVrGLKfzRfw9qa4pQOfGaKsCDi4seDOH+xC5evD8Ufv6ncjC9/dhXuXLM0\nZZUIw4IAIRQZuFmM/cWFILbUWKfXZeUkSqx6Z6yfEgyL8PsD+MLmmrknWNGzrw6NeYhzzlfNp6Hz\nKam80EgSx3vtIzj7djsufjwYX9tdu3oJvrZlNW6pKExJOwRRRCgYQiUVwMg6gWAYHQOujJ5y55zD\n5gqga9CJzkEXhmxejDr9GHX4MOr0T1pm+OKJP0lJmfaFxh8M47WWHpx92xKf1dJpVNh5ZyW+dNfK\nlM3o+QMh6FQM5Uto4CbbDNs9cPqEjF5qLIoS+kc96Bp0oXvIhRGHDyMOH6xOP6yuwKTVhimmzM2A\n1YPGdzrwysWueJGgpUUmfPXuVbjnjhUpKd7BOYfXG8CSAsOCXpWwEGXLUmN/MIyuQRe6Bl3oG3Vj\n1OGP91Oc3uCkx6tMFVMSTbAuAtjKOXcm4xuIvmdWBK5Xz7+Me+7dPm5t6WuvnMOWrTtkud+QzYuX\n3mxD88Wu+Bk8t1YW4uHtt2JNVZEs9xwrVgCjOE+HonwqgJENwoKItl47TBlW3SssSGjrs+NDyyg+\n7BhFe589vtxkMgoG6LRqGLQq6LUqqFVKnPy7L1JnaB44jwze/Pr3rbjSNgwgMku+tbYCD3x+NQrz\n5O+kiKKIQCCEylI6hy9b2F1+DDsDGXfWldsXwkedo5EKfp1W9Ay7EBamPqNSpVTE44lOq4KCMZz6\n+y9RTJmHQEjA7y5344XXWzEcrfBckKvDnntWY9umypQkWoFgCBolQzmdw5c1OvrsgEqVUWddxSr2\nftgxgg8so7jeY8eQbfr/7zqNEjqtCgZt5OxLBuDkFDEl0QTrWc75gTl/F5O/Z8YHrlfPv4xHvn4/\nvrn/W/ju/zwCAPi7//4E/qXhJ/i3XzwvW5IFAE5PEL95qx1n37LER4vuWFWCb+xYg5pl+bLdNyYQ\nDEPNJKwozacAlsFEUUJrrx2GDKnu5Yie3/TORwP4sGP0hoN6TXo1KkvzUFGah6XFkXPqivL0KMrX\nw6TX3PA9pOqg4cWgrdeO539/HW9/2A/OI3tfd2+uxtfuuSklG8jdXj+KqXJpxnN5Auiz+WDKgH2c\nnHN0Drrwzof9uHB1AJ2DzhtGkJeYDagozUNFaS6WFBjj8aQwVw/thH1SqTpoeDEQRQlvvN+H51+7\nju6hSKGyErMBD229BXffUS770kFBEBEIhlBJlUszXveQE2EpM6oahwURV9pG8M6H/WhpHYLNFRj3\nvEqpQPmSHFSW5mF5SQ6K8w3RmGKA2aS9oRjdvPdgMcZOAagC0Bx9iHPOvzPXbzD6nhkfuDjn8YTq\nm/u/BQDxr7/7P4+kpEPrC4Txn2+244U3WuNLqDavXYqHt92K5SXyVuqKVfChAJaZJImjrdcGrS69\n65ndvhBev9KDP7zfh6td1nEdoPKSHKypKsLa6mLctKIAhbmzSwQpwUq+3mEXft58FW990A8A0GtV\n+MpnV+FLn62RvRJaIBiCinFU0MBNRvL4g+ge8qR9A3rXoAuvtXTjrQ/7x40oq1UKrC4vwK1VRVhT\nVYSaZfkwzOLIFkqwko9zjnc+GsDPz30UX45cXpKDh7ffijtvLZO9n0QDN5mtf9QNX0hK6z5OUZRw\n+foQ3rjSi4vXBsdtR8g1arC2qhhrqotwS0UhlpfkzGoJYzISrG0THuKc8/MJt2Dy98yKwDU2yQKQ\n0uRqLJc3iOd/fx1n37IgJEhQMGD7pio8vP0W2UunerwBFOZqUGI2yXofkjhJ4mjvs0Gl0aZlPbMk\ncXzYMYrmC514+6P++DIdlVKBO1aV4M41S1F70xLk58xvFJwSLPm099nxv1/+CO+2RpYO5ho1+MaO\nW3FvbaWso8+CKCHgD6JiSQ4MaTjImUzOHwihc9Cdtn2c/qCAN9/vRfOFTlzvsccfzzNqceeaMtx5\n61KsqSqaV4EDSrDkI0ocv3+3B788fzW+dPCmcjMe/dLtWLVc3qqDgWAIyuiRM9l8pM9CM2T1wBUQ\n07Y0fNDmxSsXu/DK5a5xM1VVZXnRQ7XLsGKe+4MztopgNgSuTEmwYqxOP0797mM0X+yCJHGY9Gp8\nfdst2PmpKlkDCwWwzBHfLKpSQ5XiMtihsIhXW7rx4htt8cqXjAG3ryzB5zesQO3q0lmNKM+EEiz5\nfWgZxb+//GH8PK2qpXl47Eu3y15chwZuMkc6i+SMOnx46c02nLvQhUAoMrJs0KrwudvL8bnbl2N1\nRWHSEn5KsOQXFkQ0X+jCqd99DIcnch7h1toKfGPHrfMecJsODdxklmG7Bw6vkPLVT5xzfNRhxfOv\nX8fla59UvlxaZMK9tRX4zG3LUFqQvNnOZMxgbQVwKvpHDmAv5/yV+TQqGwJXJiwRnErPkAvP/eY9\nvNc2AgBYsSQXj35xHW6rKZbtnqIkwe8PoqKEAlgqjT3Ej/PIssA/vPEa7t0++SF+cvD4Q2h8pwO/\n/UN7/EOzME+PrbUVuLe2AiVmeQpsUIKVGpxzvPl+H3529gNYnZFDRj93+3I8smtt0gthjC0cFAyF\nwSQRH195G/fd94Wk3ockJhAKw9LvSvmywK5BF154/Tpev9ILMXoe5M0VBdi+qRKb1y6T5ZwpSrBS\nxx8M49TvruE/32yDIHIYtCrsvfdmfGFzjayFMDy+AApMGiwpoIGbdBmxe2H3hlOaXIkSx4WP+vH8\n71vR2huZAdeoFNh82zJs21iJWysLZemzJyPBilcRZIxVAzjJOd+YyM0ZY49zzp+e5PGMD1zpLHKR\nCM45/nh1AD/9zfsYik7Jf+a2ZfjmfetQkCvfSJHHF0CBUYMlhRTA5NbY2Ijdu3ejvr4eP/zhD2Hp\nt+Mf/v5/4Kcn/jklP4P+oICX3mzDi6+3whddt1y1NA/3f+4mbF67VPbZTEqwUisQEvD8a9fx69db\nERYk6DRKPHjvzfjSXSuT8m89WUz93n97Av964id4/tcv4qtf+dK870ESFwwLaO9zICeFFUj7Rtz4\n+bmr+MMHfQAi1UPvum05vnL3KlQvlbeAEyVYqdc/6sG//uY9XIrOJiwrNuHAV9ZjTbV8VZGDoTAU\nXKIVN2kwYvfC5g3BoEtNBdJYP/g/Xv5kD2COQYMvbK7G7k9Xy76FJhkJ1suc8x1T/Xma120D8MRk\n12ZL4Ep1mfa5CIVFvPhGG868eg3BsAiDTo0/270GW2srZdtIHgyFwbiESgpgsuKc4+DBgzh27Bj+\n7NE6MIUCPz3xz7LPooYFES//sROnf3cNTm9kxuq26mLcf89NuH1lccpmbynBSo8hmxc/O/sB3v4w\nUgijamkevnX/etQsm99eiulWBfzN3/49Ck1aGrhJkUAwDMtA6mauRp1+nHrlY5y/FFnerlYpsG1j\nJb782ZVYksQlO9OhBCt9Ll8bxL/85v340vJtGyvwyO61sh1+HltxU15iginDjhtYqOaaXM21n/2B\nZQT/X9OHaI3u2SzK1+Orn1uFe2srZJkBn0yyqgi+A6AFwAYAmzjnDybwuq0ADmVzgpVNhu0+NLz4\nbnzd6a2VhTjw1fWyVRsUJQl+XwDlS3IogMlIFCU8Wvct/Oy54wDk3Qc42azoTeVm/MnONVhbLd/y\n06lQgpVel68N4vgLVzDi8EHBgPvuWomHt90yrw+v6fa10sBNavgDIXQMulOSXAVDAs68dh0vvt4a\nKdCkYNhaW4G9996MohScwzYWJVjpFRZEPP9aK06/eg2CKCHfpMU3v7gOd922TLZBO48vALNBjdIi\n+aouj13GD0RiXFNTE3btSt0y/nQbsnrg8Amz3j4yl5ViE2dFc40a7P38zdjxqUqoU7wvfboEK6FP\nSc75XsbY4wD2AmhPMLlazzk/zxg7NPsmk7koMRvw3x7ZjDff78NzL72Hjzqt+Ot/fAUPbFmN+++5\nKenrnpUKBUwmA3pHvMg3hGQNYIuVKEpo77OBKeQPGn0jbjz3n+/Fq8qVl+TgGztuxaZb5C+1SzLT\nhtWl+FF9EX5x/ip+82YbXnqjDW9/0I8DX70D629akvT7aTVqiJKEaz02lJfkpOR8rsUmVaXYOed4\n64N+/PTs+xh1RPb1bV67FP9l+61YVkyfFYuRWqXEg1tvxmduW4p/fv5dXO2y4oe/uIDXWrpR95U7\nUJSf/KWqJoMOnlAYbb02VJblJ73q7thl/EePHgWA+KqTs2fPLooka3DUDXdQnNPe/Hvu3Y5v7v9W\nfMAN+GRVwz33bh93bSAk4PTvruHFN9ogiBL0WhW++rlV+OJdK6HXpv+MrYmmncGK7Z9ijD014akZ\nz8FijG2NJliTLiekkSF5uX0h/FvjBzh/sQtAZInPXz2wERWlubLcLxQWwEVBlgC2WAmihNYeG57+\n/nfxryfkK7QSDAk4+crHeCm6GdmoU+Ph7fJXpkwEzWBljvY+O37yfAs6+p0AgB2fqsSf7V47q7Oz\nZlM4yOcLIMegxlIauEkalyeA3lGv7MlV/6gbDS9cwXvtkSJMVWV5eOzL8lemnAnNYGUOSeJovtiJ\nf2v8EL5AGAadGo9+cR22rC+XZUBPkjh8/gCWFRqRa0reHvWxy/jr6+sBIP710aNHF/zgZM+QEwGB\nQ6ed+1LPRKp1v/VBH/7lN+/HizDdW7sCf7JjjayVKRMxnxksS/T3i4hUD0xIbPZqFm0kSZZj0OD/\n+NoG3H17OZ751WV09Dvx+DO/w8Pbb8GXP7sq6efcaNQqSEolWnvsWFpkRF4SA9hiFAwLsPQ58ce3\n34gnV7HpcyDSKd1y7/Z57wX80DKKnzx/GQNWLxgDtm+qxH/ZfivyTDRzQMarWWbGkb/YghfeaMMv\nmq/i5T924krrMP7ygVqsqUpsw/prr5wbl1DFTPbzbDDo4A8LaO2xorIsP+VLPxYam8uPYWdA1uRK\nFCW89Gbk5yMkSDDp1fjGjjXYtknes9VI9lEoGHZ8qgobby7D8RdacOHqIP7x9CW881E/DnzljqR3\nnBUKBpNRjwG7Hy5fEMuK53f+UQxjLD5zdezYMQBYFMkV5xxdAw6ITCnrOVd2dwAnXrwS3w9csywf\n+758O24qL5DtnsmS6B6sPAAFAGwA9gM4xTnvnOb6PdEvC6PX7+Oct0y4hv9fj/9t/M+b7/ocNt91\n92zbTxLgD4bx099+gHMXOgEAq1cU4K/21qJMps3kvkAQerUC5SXJCWCLjdcfQteQGyajDowxWQqt\n+INh/Fvjh2h6pwMAUFGai2/dvx6r0hy03nrz93jrzdfjf/7R09+f1WgzxZTU6Bp04senLqFjwAnG\ngC/etRLf2H5rQofAzvbnmXMOjzeAsgIDzLnpOQQ32w2OuuEMCEmr7DXZv+GpMy/gwlAe2vscAIDP\nb1iBP//C2rQv8xwbU8JhEc/86DDFlAzDOcerLd147qX34AsKyDVoUPfVO7B57TJZ7hcWBAihMCrK\n8qBVz39p2dhZLGDhJ1iiKKFjwAGlWg2Vcn4DX9Otarj7a3+Jn/72fXj8Yei1KvzpzjXY8akq2Yq3\nJWpsTBHCAv7pR0fmVeTiJIDjiOzBsiByDtamBF63D8AT0evfnfAcTb2n2OVrg3jmVy2wuwPQqpV4\nZPda7LqzSpYgIIgiQoEQKkpz03aKdzayu/wYsPuQY5SvI3n5+hCefb4Fo04/VEqGPVtW42v3rJb1\nbJK5oiWCmSssSDj9u49x5rXrkCSO5cU5+Ku9tVi5fH6VBqfiD4SgVTGUl+Sm/QM2W3DO0TPkQlCc\n3+2dqlIAACAASURBVBKesSZuSg8LEv780Tq8cfbnWLXrcdSs/TQO3L8eG2TYozdftEQws404fHjm\nzOX40tK77yjHY19aJ0ulQc45vL4AivN0KMqfexXLxbZEMBQWYel3QKfXQqmQ5+iOJx//a/z8Zw1Y\ntetx5JXfjg03LcGBr8qzR2++klamfczvFxM9B2ua96TAlQZuXwj/70tX8PqVXgDAHatK8Jd7amU7\nN8vjjR76R6WXZ5TsUeaJAiEB//qb9+MzmTXL8vGXezagojRPlvslAyVYma+1x4Yfn76EvhEPFAqG\nBz9/M/Z8frUsS8IEUULAH0T5Eiq9PJPYKLNCpYJalbwN4GNHnB/8k8fQ0jqM1ndeRMnanXis/n/g\nkV1rYdBl5qAaJViZT5I4mt7pwM8aP0AoLKIgV4f6vRtxW408VWwDwRCU4HM+M2sxFbmIFciJra5J\nlrEz4q+1dOP4C+9iqP0ylt20Ef/1Pvn25SVDMhKsc4jsw2IAfonIEsGV82nUQg1cnHOIohQ/mR6I\nrP1VKFhSsv1k+cP7fTj+wrtw+0LINWrwfz5Qi9rVpbLcKxgKg4sCKkrzE1pCtNhIEkfngAMSU0Cr\nkadj0t7nwI9+eQF9ox6olAp8fdst+Mpnk3N4rJwWWoI1l+WeoiRBkjikMTFFqWBQKhUZ86ETDIv4\nj3Mf4aU32gBEjoiof3AjimUacfT6AjDplEnbR7HQxMqwGwzJGWWeSJIkPLrvL3D+xX8HAFTW3odn\nnvkn3FZTkvR7JRMlWBGCKEGSJMS6f4wBCoUiowpU9Y968I+nL+Fatw2MAffffRO+vu0WWdoYOzOr\nrNCI/DnsH18MZdpH7F6MuoMwGeQZjPcGwmh44d344P+nbi1D3VfugDnNRSxmkowEqxrAHgANAB4E\ncHHinqrZWgiBKxgSIAgCwDlUSgU0SgaFkkGrVkGpVECBSGUQQZQgihJCggSRc4SFSAKmVCqg0ajT\nlnjZXH78+PQlvNcWmY6/7zM1+NOda5KaBMU6lADg9QZQmKvF5T++saACz3wEwwI6+53Q6LSyfHBI\nEseLb7TiP859BEHkKC/JwcGHNqGyLHNnrcZaSAnWTOd93HPvdgSCYYiSCCUYVCoFVAoGjUoR/Try\n8yEhugQ3LEISOcIShyBIEMGgUStlS9ITcaVtGD8+dQl2dwBGnRrf+tp6WfdRhINhrFiSA71OnsNK\ns5HN5ceQwweTQZ5lxk5PEM/86hJ+9a//C8MfNAEAHnn0AP6fH/yvjE92F1uCJYgSgqEwIElQKhjU\nKgWUCgaNSgmVSgFl9N9L5JEYEhJECCKHEI0pTKGARqNKW4EZUZRw+tVrOPXKx5A4sGq5GQcf2ohS\nufaP+0PQqRmWF+dk/OBjqnyyzBiybfe42jmKH528hBGHD1q1Eo9+aR221lZkfDwBkpNgzarIRSKy\nMXBxzuEPhABJglajRK5RixyDZk7Bh3MOfzAMhycIX0BAWJSg0aihScKGy9mQJI4X3mjFf7z8EUSJ\no7IsD3/90EYsL5l/OffJOpT/93e+jZ899yxefOk/8aUv3jfve2Qzm8uPIbsPJpn2W1mdfvz41CW8\nb4kk0Ls/XY1Hdq+FNotmERdSgjXVZt4//WYd/vt3/wF6nQr5Ri2Meu2c9hgJogSvPwSnJ4hAWITI\nAZ1Wk/JR6UgH/DIufjwIIFKZ8r/ed9u8DieejscXQJ5BjbJCU1Z8IMtFjv1WE73bOoxjpy7g/XPP\nYfiDJuz62iNYWmRK+tERclkMCVYoLCAUCkOjUsCkUyPPpJ1zxzgYEuD0BuD1CwiGRTCFAnqdJuX/\nxlc7R3H05EWMOvzQa1XY/+Xbcc/6FbLcSxAlBAOR2azFXg05GBbQOeCEVquBcp7FLCYjihJOvvIx\nzrx6DRKPbFs4+NDGrDqaIxkJ1pyKXMzwnlkTuEJhAeFQGHqNEoV5ephkqIokSRwOTwB2dwAhUYJW\nM7fEba5ae+340S8vYMDqhUatxDfvuw3bN1XOK5BOVx3mb77zdyjM1WFJweLbmyVJHD3DLgQFLtvI\n+7utQ/jRLy/CFV0C+pd7arHxZnmWgMppISVYwI3nfTy6/y/wzD/+GFoZko9QWITN6YPLHwKHAjqt\nJmXFITjnOPu2BT87+wHCgoRlxSb89dc/hSqZZk7DgoBQMIzlJYtzb1YgGEbXoAsanWbeVb0mI4oS\nfnH+Ks68eh3OnitobXwaD//Z/v+/vTsPk7MsE/3/fWqv6n1POumQlbCHbMgiEAiYIKIgEHAWZkQB\nBxfEo87MOZ5LPT/PDIJDYGRQQDnqKLIIjDpIEggGFUVICDsCIfvS6e70Ul3bW+/y/P6oqk4npJPu\ndL219f25rlzp7nTX+3a66u7nfpb75pbbbgcOXIkdb+sIN1VqgmU7DslUGr8HGmvD1FeHXHmtxxIG\nvdEUCcPC4/MSdimRP+S1k2m+//jL/PH1XQCce2oH1310nmvn/RLJNAGvpqOtrqS2ThZKT3+c7oEU\nVZH8nrfK6Y0muf3BF3lz676hLaBXLT2+JIttHY4UuThKqVQa7dg01IRoqosUbHBi2w49/QkGEgYo\nD2GXih4cLGmY/ODXr/Lbl7YDcPqJ7fzDZfOpibjTQC5tWtimSUfrxNniE0sa7NgbIxQK4HMhgbYd\nzSPP/IVHfvsXtIZ5s1v5wpULS34f80gqKcFyHE08keS2b32NH/3wHqBw5XyNtMXe3jgJwyIQ9Oe1\n6MHhbN0zwO0PvsjO7kF8Xg/XLD+Ri8+c5dr3G0+kiAS8TJlAW3z27ouxL2a4Vnm0bzDFygdf5PUt\nPXgUXH3BCTTa2zhvaX5bRxRCpSVYlm2TSqapifhobagu6BnngcEUPdEkaVsTCR3dqvtYaa1Zu2Eb\nP/z1qximTVtjFTdftci1nki245BMGDTXhWhpOPpKg+XEsh22dw5g43FtS+Crm7pY+dB6BuIGDTUh\nbr5qESfNdKeIidvG02g4Ryml/hV4SSk1H6jP6x2WmFQqDdqhtSFSlCVir9dDW1M1bU3VROMpuvqT\nWLYmEg66OhALB/18/oqFzJvdyj2/fJnn39jNpp19fHHFIk4YZSPRsQj4feD3sa0rVvGDIq01u7qj\nxFI21S41+uyPGdzx8Iu8uqkbpeDqC47n8iXuVHMTo6e1Jp40CPsU37v9//CjH95zQDlfwPUkKxjw\nMW1SHY6j6RmI0zuYxOvzEXL5vNb0yXXc9tkl/Og3r7P6hS3c/8RrvLypi89fvtCVZtZVkRCW7fDu\nzj5a6sM01ZVeWd98MUyL7Z0DKK/PteTq9c3d3P7Qi/QPGtTXBPnSVYuzA6G5B3yeUqrkk6tKYtk2\nRipNfVWAY6Y1FqVtQV1NiLqaEGnTpnNfjFjSymxJdnHnjVKKCxZN57hpTax86EW27Bngf93zOz5x\n4QlcevacvP8/eD0eqqvD9CdN+gb3VfxkcF80SWdfgnA4iN+V4jiaX6x7m4fWvoXWcMqsFr541WLq\nXfhdUAqkyMUwadPCMk0mNVRRV2Iz/inDZHdPLDNb5HKiBdDZG+eOh17knR19eBSsOP/4MZdePtwW\nwYP36ufKL1fiTFE0lmL3vjhBl7bvALy5pYfbH3qR3miKuqogN1+1iFNml3ZFr9Eo9xWsRNIg4IX2\nlhp+u/bpkirn2xdN0t2fQHm9rp3ZGe75N3Zz92MvEUuaNNSE+OIK90ovA6TSJtqymNpSQ8SFPjrF\norVm774YvfE01S5t33EczeO/e4efP/UmjoaTZjRz89WLy3YlPKfcV7By1e7qqwK0NVaXVD8423bY\n2xdnIJZ2bYfGcKZl89PVb/Dr594DCrNbI55IEc5OBlfStkHTstm+N4qDcu13wUDM4M5H1vPyu10o\nBVeedxxXnn9c2U8Aj3uLoBtKKXDlloGb6oK0NpT2mSAjbbGrexDTgYjLZw0s2+HBp9/i8d+9g9Zw\n4oxmblqxiOa60c2WHqlq2qFmPHPbBtsay/+AqWnZ7OyKkraVawM8rTX/9ft3+dmaN3EczQnTm/jS\n1YtprHWvUXEhlWuCZaRNbMtiSsuBZ4JKsZxvXzRJV38Cr8/negXCnv4Edzy8fmjf/eXnzuWqpce5\nunKdS3KntNSWfZuIaCzFnt44/oB72zwHEwZ3PrKBl97eC8DlS47l6qXHV8TugnJOsMplcO84ms7e\nGAPxNOE8NaM9nA1vd/LdRzYQTaSpqwryhSsXMt/FJte5JLehKtPfs5SLuhxJbrKmL54mEnbn3B7A\nX7bt4zs/f4HeaIraSIAvXrWIU+eUXiPyo5GPM1jzgUeAPuBh4D2t9WPjualSCVyJpEHIp5jaWltW\nv0ASyTS79sVAeVyffX5lUxd3PrKe/kGDmkiAz12+gMXHTx7V1x5N3x/INP/DcZjUVEWNC0VF3OQ4\nmt09UaJJiyoXg1Ysmea7v9jAi29lqrVdes4c/vrCE8rqeXwk5ZZgOY4mkcy0Iyj1yZqDdffF2RdN\nubrSCpmZ7kd++za/+G2m9PLcaY3cfNViWhvc286X+bkYRIJe2puri1Z2+mgZaYsd3YPYjnuTNQDv\n7OjlOz9/gZ7+JNVhPzetWORaf8RiKMcEK7ezpqPMVmJt22FXzyDxlE1VxN1dN73RJHc+vL9i7qVn\nz+ETF57gasGE3DbNxtogLfVVZZdo9UaTdPUlXD2Tq7Xm189t4j9XvYHtaOZOa+R/fOK0UU/Sl4N8\nJFjrgQuAe7XWKyqhyIVt26RSaaa0VJfdAH64gcEUe/riBFyc0YTM+Z5/zy7vAlx8xiyuuehE1wcq\niWQaj3Joa4hQW1XaK1qOo+nqjdFXgC0S7+3q47YHXqCrL0FVyM/nr1zIaaNMestJOSVYKcPEg8O0\nttqyG8DnDJ99dnNGEzLne+54eD290UzPrM9+fD6nu9QzK8d2HBJJg+qgj0lNhS0KcDQM02J39yCG\n5e7WcK01v/nTZn785GtYtmZORwNf/sRprjWKLpZySrC01sQSKRqrAkwqo7LVBzNMix1d7k8O2Nlt\nrQ8+/RaOo5k9tYEvXb2YSY3uHjlImxamadJYUx6J1sBgir39CZTH3cn5eDLNXY++xJ/f3APAJR+c\nzd8uO7GkV1+PRl4SLK31IqXUw9kEa43WelwnWosZuBIpg7Dfw9SW2pLaw3y0CrXM6ziaXz23iZ+t\nzsxGzJhcx5euXsyUFveDfzJbeKSpNkRjbbikgphlO+ztjRGNm4TC7s7+a61Z/edMsQDLdpg1pZ4v\nf+I02lz+JVIs5ZBg5Vat2hoiFbM1sxDbWwGicYO7Ht3fM2vZaTP4+4tPdr1Xm+NkC4/4FW0NVSW3\nMpBIpunsjWPYmiqXz9wmUiZ3P7ZxqPz1xWfO4prlJ5VdueTRKJcEK7dV/phJda60cCiG3Flkt6uY\n/mXbPm5/6MWhnlmfufRUzp7X4dr1cnKtImoiftoaq0sqkdBa0zeYoqc/gfJ4CblcqGPz7n5ue+AF\n9vbGiYT8fO7yBZx+Yrur1yyWfCRY9wAamAm8BMzUWq8Yz00VI3DlBkLtFdpAzrRsduyNYmnlaqWb\nd3f0cvtD69nbGycU8HLdR+exZP60giQ9RtrEMi2qwj5aG6oIFrgx83DxpEFXX4KU5RAKBl0PqEnD\n5PuPv8zvX90JwPIPzOCTF59ctqslo1HqCVbatHAsk+mT6yvy5xCNZwu0BN2bONi/evI6lp1ZAfzS\n1YuZ1jb+ZuejuXYilcaDpr46QHNdVdEm3bTW9EaT9EZTOKiCNHTdsmeA7zzwZ/bsixMO+vjsxxdw\n5snuriIWUzkkWPFEitoKbZw9fDLYrf5KkNk+f/djG3n+jd0ALF14DJ+65BTXmp0PZ9kOyZRByOeh\nuT5c1J03pmXT1RdnMGHi87t/xlZrzVMvbuWH//0qpuUwo72Or3ziNCY1ldd2+bHIR4I1A7gQWEim\nguB9472pQgcuI22CYzN9cn1JzSy4YSA7U+RmydREyuSe/9o/2D/n1A5u+Ng8wi71TThYrrGiV0Ft\n2E9jXaQg232MtEXPQIJYygS8hEP+gvwS3NY5wHceeIFdPTFCAS//cNn8gszKFVspJ1jxRIr6iL+s\nt++MhtaaPftiDMRNV89SbN7dz7/9/IW8NjsfC9OyMAyTgM9DU02IWpeatR4sGk/RG02RStv4A/5M\n+wqX5foJ/eBXr5C2HI6ZVMtX/uoDtDdX7kAISjvBsh2HRCJFR2tNWR9bGI20abO9K4rWyrXVFK01\na17Yyv974lXSBWh2fiipVBrbtokEfTTVhagqQBN023boG0zRH0uRtiEcChRkzJs0LO795cs8+/IO\nAC5cPJ1PfeSUkt+GPV75SLA2aa1n5/OmChm4JspAaDjH0ezsjpIwbKoi7sygaK155qXt/OBXr2CY\nNpMaq/jS1YuZPbXBleuNxLJsUkYar0cR8nupqwlSHQrkpdiDbTvEkmkGYgaptI0DhEIB1ysjDffM\nhm3c+6tXSJs209pq+fInTmNq68R4LpdigpVrGDytreaACoGVzkhbbOscwOt3LwlIGhY/+PUrQ83O\nzzxpCv9w2alUFXgLn5E2MU2LgM9DJOijvjpEKOjLS7JnmBbRmMFg0iRt2ni8XkLBwkzUAKTSmYHQ\nuo2ZgdAFi47hU5fMc31bZiko1QQrbVpo22LG5PqKKlJ0JL3RJHt7E4Qj7lUb3NYZ5fYHX2BH1yB+\nn4e/u+gkLjp9ZkFXB7XWpAwTx7YJBbzURALURIJ5ST601iQNk77BFEnDJm07BAs0UZOzY2+U2x54\ngZ3dg4QCXm64dD7nnlr5E8CQvy2CC4GnAAVorfU/j+emChG4clsCp5Z5IYvxiCUNdnbFXK0MtrNr\nkH978AW2dUbxeRV/s+xEPnLm7KJstdFaY5gWpmnhUwq/34PPowgH/YQCXnxeD16vB8+w4OpojW07\nmaV9wyKZtrBsjWk5OBp8fq/rDVkPxUhb/ODXr7J2wzYAzlswjes/Oq9i9uSPRqklWLmB0ERYCR/J\n3n0xemOGq1t8nt24nXt++QqptEVLfYQvXb2IudOaXLnWkdiOg2GYOI6Dz6MI+Dz4/V5CAR+hgHco\nnuRiiibzu8e2HdKWTcqwSJk2ppWJMcrjwe/3FWVL6c6uzEBoR9cgAb+XGz42j/MWHFPw+yiWUkyw\nJuIE8HCW7bBj7wCm497RBiNtcf8Tr/HUi1sBOO34yXz28gXURIpz9jKdHaOgNX6fB7/XQ9DvJRT0\nEfBlY4pHkXuSajJxyLYdUmmbVNoinYspjsbj8RAM+gs68Zu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hG1pDVcjPJR+czUfOnFVW\nlTq11jz/xm5+/tRb7OweBODUOa186iOlM1ljWjaWZeM4DlprFAeOUSAzRtEovB4PHo8i4PcVfEtu\nPvpgzQceAfqAh4HNhytyMRqjDVy5LTyzptTLFp4isrMBzHE5gDmO5nev7OBna95k30ASgOmT61hx\n/nF84ITJJTGYGEnatFn15808tu4dotmS0QvmtnHtxScXdUbTtGzSaROlNT6fh6DfQyQUIBzw4fd7\nRzyArbXOHNS2bJKGRTxlYloOpuWAUgQCftdfk24kWENbeCZNvHL4q1at4qKLLuKmm25i5cqVANx8\n883ceeedPPnkkwVNsuLJNNu7Bl1rdp4TS6Z55Jm/8OTzW9i3dSPvrrqN+Usu5667vsvU1toxFbko\ntK6+BA+tfYtnN27H0ZkzbR89azYfX3JsUSdrjLRJ2rTweRQBn4eQ30sk7Cfo9+H3eUcc5DiOxrRt\n0mmLZNoimbJI25k44/F4CAb9rj4X3EqwYvEUkxsjUqyoyPbui9EbT7s6cQOwZXc/P/rN67y2uRuA\n6rCfS86azcUlnmhprXllUzc/W/PG0ER2W0OEv7vopKJO1jiOJmWk0Y6Dz+sh4PMQDvqIhDJjDL/P\nM+K92dkximHaxFMmRtrGtB0sR+P3+wi5OF6F/CRYLwIXAvdqrVeM1Dx4LEYTuHJbeGa2yxaeUtHV\nF2Nf1L2mfzmmZfP0i9t49Nm36Y2mAJjaUsPFZ87i3PkdJbESlBONG6z+8xaefH4z/TEDyFRM/OsP\nncAJM4qzhzltWqTTJgGfh5qIn7rqUF7LBBumRTRmMJjMBDSvz0so6M97gM53gjXRt/BorYcSqptu\nuglg6O2VK1cW/BdsbuLGzWbnOT39CR599h0efeyXVLWfjMejWDh3EhefMZPe7a9wXgklV5t39/Pr\n5zbx3Ks7sWyN16O4YPF0rjxvLo1FOH+stSZlmGjbJhTwUlcVpKYqmLffy1prkoZJ32CKpGGTth2C\ngfEXMDiYGwnWYCxJR2s1NRE5ulAKEsk02/YOEgq70+x8uNc3d/Pg02/x5tZ9AERCfpYuOoYPnz6T\ntsbSWcm0bYfn39jNr57bxLs7Mj1IG2pCXHneXJYuml6U0uuW7ZBKGfg8inDQS2NtmHAexxC27RBL\npumPGRhpGwcIhQJ5n8DJR4K1Xmu9SCn1cDbBWqO1HtdvoyMFLtOycCyLWVOk2WepSabSbN07SCjk\nfgBLmzZPvbiVx3/3zlCiVRXyc8HiY7hw8fSiDpS3743ymz+9x7qXtpO2HABmtNfxVxeewIJj2wr+\nvM0ErDR+b6ZEdn11/osJHIrWmsGEQV80RTJt483jrFE+E6xE0qCxOjDht/AMT7KAoiVXw3X3xemO\npqipcj956O5P8Oi6t3lmw3YsO/O67Wit4cNnzOKDp0yhyuUzFSNtMTx7yQVseGcv//2HTby+pQfI\nbLP74LwOrl563CHLzrstbVqkDZNI0EtzfZiqAp1/tm2HvsEU/bEUaVsTDgbysp0wnwmWHF0oXY6j\n2dbZj+UoQi5XhtVa8/rmHh5auz/RUgoWHzeZ5afP5ORZLUVrmTCYSPPbl7bx3398j57+zI6g6rCf\nS885lovPmEmwwBPVWmuSKROFTW04QGNdhECBSt8baYuegQTxlIlDZhdPPn7n5SPBuodMc+GZZMqv\nz9RarxjPTR0ucBlpE5/STJ88vgPJwj2Oo9ne2Y+p3Z95hkzy8Pzru3niT+/x9vbeoY/PmlLP2fOm\nctbJU2mqc39w1jeY4k+v7+K3L20fWmIHWHTcJC45azYnzWwu+EA1t1pVG/HT2lBV1K20WmsGBlP0\nRJOYTqZB5HhmjPKVYEn10f1KMcECSBkmWzujmVnGPDc7P5T+mMGaF7aw+s9b6BvMTN74vB4Wzm3j\n7HkdLDxuUt773hzch0trzf/40hd59Gc/5NTL/ie+5hMACAd9XLDoGC4+cxatB00IFOIMWDxp4EXT\nWBuisTZc1OeGZTv09MWJJtOgvONqpZCvBMtxNIlkilnt9QUbIIqx6+mP0zVQmIkbgE07+3jiT+8N\nrTwD1NcEOevkqZwzbyqzp7q/YJA2bV7e1MW6lzLN13OTSFOaq/nIWbNZMr+j4ImV7TgkkgZhv4fW\nhkjBJmpGkjJMuvoSJAwL/zhXysedYAEopa4HFpBpOjzuCoEjBa6hBsKtE+98RDnqjSbZ25egKuJe\n07+Dvbuzj1XPb+b5N3aTNDJN3pTK9IGZP6eNeXNamZ2nM3uW7fDern5e39zNi2/t4d2dfeReMpGQ\nn7NPmcrFZ85iamvhV9KSRhpt2zTXhYs+CDqUtGmzty9GLGERDB1do9l8JFixWJKpLdXUVMkWnlLb\nIngwx9Hs6IpiWLpgPclMy+FPr+9i7fptvL6le+j1HQr4OGVWC6fOaeWU2S1Mbqoe9/+P1pqv/dOX\n+c/7v88HLlhBZ1+cbRueoPWkZXSc/jdMaanhwsXTuWDxdKoOcZZjvI2Sj3Rv8aRBwKuY1Fj8QdCh\nDCYMuvoSpG1NJBQc8wp9PhKsXAPhmVOkgXA5SBkm2zqjBEIBfAWYuIHMROxTL2xl3cbtdPbuf/60\n1Ec4dU4r8+e0cuLM5rxsK9Va09kb540tPbz09l5efncvqXSmobZHwSmzW/nwGTNZcOykgheAsCwb\nw0hTHfbR1lhdcnUUHEezbyCRmWDzeAiHxv7zyEuClW+HClyJlEF92E9bEbZCiKNnmBbb9gzgCxzd\nIPror2vz0tud/P6VnQfM1EBmJnpGex2z2uuZ0lJDe3M1TXVh6quDVIcDBwQax9EYpkVvNEXPQJK9\nvXG2dUbZ1jnAe7v6MUx76HP9Pg/zZrdyzqkdLD5+clE6u6fSJo5l0VofKYsVGcfRdPfH6YsZ+P1j\nmy0aT4KltSaeSDG9rUYaCGeVUpGLw+mLJuks8MQNZCaMnnt1F797ZccBK9SQ2VpzbEcjx0yqpb2l\nhvamKhpqQtRVBwkFfAfcp2U7JFIm+waSdA8k2d0TY1vnAFv3DLCtc4Dtf/opXa+vBqBj/of52xv/\nJ+ctOIZjOw4/wz1SH66xVEE81GMmsonVlJaags9uH420adO5L0bcsMa0VX28CVbu6MLM9gZpIJxV\nClVJj0TrzMRNMq2JFLCsutaaTbv6+f0rO/jDqzvpHzQO+PfJTVXMntpAR2st7c3VtDVGqKsOUVcV\nPOBclNYa03KIxg16BpL09CfZ3rV/jJI7PpEzs72eM0+ewrmndhRkZ8/BLNvBSBnUVgVoa6gqixoK\n0XiKvX0JHK2IjGFyqSwSrFgiRVt9uCgHeMX4aa3Z1R0lbjhjenLmS9KweGNLNxvf6eK197qHSo8e\nilKZUsE+rwet9QEJ1KFMaanmxBnNnDq7lVOPbStagY20aWGmTVobImX5OtFa0xvNDDh9Pt+oqlEe\nbYLlOJpEIsWsKbKF52DlMCCCzCB6W2c/Hl/+ix2MRk9/go3vdrHxnb38Zdu+oQI2h+LxKHwehdfr\nwbScAyZ7Dub1KKKvPcxbf/wlAJ+87ka+8X9HnxwNT7JgbI2SD5ZIpvF6NFOaqspyEsKyHTr3DTKY\nHF2iNZ4EK3d04ZhJdUVf6S0V5TJhk9M/mGLPvjiRSGHOJw9nO5rNu/t5+Z29vLKpi027+kkfZuzh\n82bKjyulSJsWzmGG6rWRACfMaObkmS0sOn4SLfURF76DI3McTSKVoibkY3JTTVkkVgdLJNPs7o1j\nO4xqLHu4BGu0jYYPLtP+ntb6sTHe94hi8SRTmqqorZYSp+VKqcy2zmgsxa59cddLLx8sHPSx6LjJ\nLDpuMgDxlMmmnX1s74yys3uQPT2x7KFpg3jKxLIPHAQF/V7qa0I014Vprg8zra2WYybVMXNyXdFL\n79qOQzJh0FgTpHVSY9n+cldK0VQXoakuwr6BBF39SQIuVArLbeGZ0yFbeA7l4EGPUqrkBkKQKUk+\np6OJ3T2DRF1qdn44zfURLlw8nQsXT0drTXd/kk07+9jZNciu7kE6e+P0xwwGYinSlkPa0ZAtduPx\nKMIBH011YZrqwrQ1RJg+uY5pbTX87Pu38OM//vKAFSilOOok6WgYaRPbspjcVEWtyxVh3eTzepja\nWodlO+zuGWQwblAVzv/gOWWYhP0wtVXOhQ+3bNkybrrppqHznLB/y/GyZcuKeGeHVl8ToirsZ1vn\ngGvNzkfi9SjmTG1gztQGrjz/uGzvriibd/ezu2eQXd0xuvsTDMQNovE0lq2x7AN3z1SF/TTXRWiu\nCzOlpZpjJtUxfVId7c3VRV9RjSdSBH2K2e3l3VIpEg4we0qARDLNrn0xHO056lXP0Y5s7gMWkSnT\nfptSaj0w7gQrU4Uns4WnkMu2wj211SGqwgG2dQ5gFqD08kiqQn7mzW5l3uzW9/2b7WjsbIKllCLo\nH7lvS7HFEykiAS/HdlRWq4KmuswqXFdfnL7BJME8VQmzbBvbNJk9tbFkf6ZibNqba6hNGuzoihWk\ncumhKKVobYjQ2vD+mWGt9f6Y4mj8Xs+IfVvWrV3Dj3/wvQPOUEEmyVpy/oVHPEM10hZBGF2Cltu6\n01QboqWhcs45+7weprXVYVo2u7sHiSXtvG0vlaMLI1NKDa1clVrRnJH4fV5mT23M9MyKpVxvOTMS\nn9fDrCn1zJry/qQ904My0x/O0ZrgYfpVFpuRPbIwraWyxvGRcIA5UxsZTBh07ouDxzPm8eyop461\n1v3DXjC9h/vc0YrHU8yWLTwVx+v1MHNKA919cXqiyYKfozgSr0fh9XhL+nmXC1rHtFbu+SGlFG2N\n1bTUV7G7J0o0nh737LNybGntUIGqw0HmdgTYvneApElJvSaUUvi8Cp/Xw5E2lCx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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "mc, mi = fit_and_display('141201_at')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Viewing the results here, for the independent model two of the fits adjudge there to be *no signal*. The constrained model shares information across the fits and can therefore determine better parameters. We can compute the ratio of the likelihods given:" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "-2.69115843672\n" ] } ], "source": [ "print mc.log_likelihood() - mi.log_likelihood()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As a second gene, we consider `141200_at`. This gene turns out to have a more consistent response across the three repeats." ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "

\n", "Model: independent gp
\n", "Objective: 56.9718543123
\n", "Number of Parameters: 7
\n", "Number of Optimization Parameters: 7
\n", "Updates: True
\n", "

\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "
independent_gp. valueconstraintspriors
sum.mul.rbf.variance 2.09052725197 +ve
sum.mul.rbf.lengthscale 2.15096358834 +ve
sum.mul.coregion.W []
sum.mul.coregion.kappa (3,) +ve
sum.bias.variance 47.3972473373 +ve
Gaussian_noise.variance0.583374639802 +ve
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "\n", "\n", "

\n", "Model: joint gp
\n", "Objective: 49.078643542
\n", "Number of Parameters: 10
\n", "Number of Optimization Parameters: 7
\n", "Updates: True
\n", "

\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "
joint_gp. valueconstraintspriors
sum.mul.rbf.variance 1.6733336308 +ve
sum.mul.rbf.lengthscale 2.25933047866 +ve
sum.mul.coregion.W (3, 1) fixed
sum.mul.coregion.kappa (3,) +ve
sum.bias.variance 47.024207916 +ve
Gaussian_noise.variance0.466843134315 +ve
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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oXTOa2TJg/rYdf7Oj3e9XPsm0q2Z2OxsdChv4gyGEEOh68mqiWi1mmnwBXF4/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\nseWzdvXH+cJ/PkfPgMGqpdP4zJ9emFOb6qlOIml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cxO3Sqa8M0tYXJzCG3c+brliAz6Pz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XROxgCSGyO7uIlLKpG21LKw3NXpa++B4HT9RjMhq458sTmX/Z6JjeyRVCcOuc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\n05l37YKYTvHzB4I0u7y43V7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nfvgIzxU/w92L7ufuRfdT9ckmDr31PC9t7nifPYNB4NOg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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "mc, mi = fit_and_display('141200_at')\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Naturally, the likelihood still favours the constrained model. \n", "\n", "### Outlier Detection\n", "\n", "The above model used a Gaussian noise to fit the data (i.e. it assumed that gene expression has a log-normally distributed noise). In the next example we will relax this assumption and use the *Laplace approximation* to fit a model with a Student-t noise model (degrees of freedom 5). This makes the analysis less sensitive to outliers." ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "collapsed": false }, "outputs": [], "source": [ "def fit_probe(id, independent=False):\n", " \"\"\"Fit a set of probe repeats as either independent or correlated.\"\"\"\n", " \n", " # set up a likelihood function, Student-t with 5 degress of freedom.\n", " likelihood = GPy.likelihoods.StudentT(deg_free=5)\n", " # use the Laplace approximation for inference.\n", " inference = GPy.inference.latent_function_inference.laplace.Laplace()\n", "\n", " # set up the covariance function as before.\n", " lengthscale = 3.3\n", " if independent:\n", " kern = GPy.kern.RBF(1,lengthscale=lengthscale)**GPy.kern.Coregionalize(1,3, rank=0)\n", " name = 'independent gp'\n", " else:\n", " kern = GPy.kern.RBF(1,lengthscale=lengthscale)**GPy.kern.Coregionalize(1,3, rank=1)\n", " kern.coregion.W[0] = 1.\n", " kern.coregion.W[1] = 1.\n", " kern.coregion.W[2] = 1.\n", " kern.coregion.W.constrain_fixed()\n", " name = 'joint gp'\n", "\n", " kern += GPy.kern.Bias(2)\n", " \n", " m = GPy.core.GP(X, Y[id][:, None], likelihood=likelihood, inference_method=inference, kernel=kern, name=name)\n", " m.optimize(messages=True)\n", " return m" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "

\n", "Model: independent gp
\n", "Objective: 70.2981190262
\n", "Number of Parameters: 8
\n", "Number of Optimization Parameters: 8
\n", "Updates: True
\n", "

\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "
independent_gp. valueconstraintspriors
sum.mul.rbf.variance 9.02815616863e-05 +ve
sum.mul.rbf.lengthscale1.23195228302e-15 +ve
sum.mul.coregion.W []
sum.mul.coregion.kappa (3,) +ve
sum.bias.variance 12.0830497819 +ve
Student_T.t_scale2 1.40327776475 +ve
Student_T.deg_free 241230.532918 +ve
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "\n", "\n", "

\n", "Model: joint gp
\n", "Objective: 68.3173355645
\n", "Number of Parameters: 11
\n", "Number of Optimization Parameters: 8
\n", "Updates: True
\n", "

\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "
joint_gp. valueconstraintspriors
sum.mul.rbf.variance 1.72362972802 +ve
sum.mul.rbf.lengthscale3.33382235324 +ve
sum.mul.coregion.W (3, 1) fixed
sum.mul.coregion.kappa (3,) +ve
sum.bias.variance 15.5408413253 +ve
Student_T.t_scale2 1.9462960868 +ve
Student_T.deg_free 197085.121973 +ve
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VukRQEqNYSJxTp07p4MGDevzxxzU1NbXlsYmJCWUyGR0+fFgTExO6d++e5ufndf/+fbW3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\nAAAAQJ0V5lwVLguUHo5kMYr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sQjIJ5xwdAw5o9VqagZWRUqGIlHXnuNJjg83lS3WTCJGFPxBCz7AbJmN67OOM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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "mc, mi = fit_and_display('141201_at')" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "collapsed": false }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ " /home/maxz/Documents/gpy/GPy/inference/latent_function_inference/laplace.py:225: UserWarning:Not perfect mode found (f_hat). difference: 0.000577364331264, iteration: 30 out of max 30\n", " /home/maxz/Documents/gpy/GPy/inference/latent_function_inference/laplace.py:229: UserWarning:f_hat now fine again. difference: 6.92839415066e-05, iteration: 8 out of max 30\n" ] }, { "data": { "text/html": [ "\n", "\n", "

\n", "Model: independent gp
\n", "Objective: 56.9719772327
\n", "Number of Parameters: 8
\n", "Number of Optimization Parameters: 8
\n", "Updates: True
\n", "

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independent_gp. valueconstraintspriors
sum.mul.rbf.variance 825.413920886 +ve
sum.mul.rbf.lengthscale 2.15105493755 +ve
sum.mul.coregion.W []
sum.mul.coregion.kappa (3,) +ve
sum.bias.variance 47.5224357048 +ve
Student_T.t_scale2 0.583366971663 +ve
Student_T.deg_free 25080.1532746 +ve
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\n", "Model: joint gp
\n", "Objective: 49.0786466464
\n", "Number of Parameters: 11
\n", "Number of Optimization Parameters: 8
\n", "Updates: True
\n", "

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joint_gp. valueconstraintspriors
sum.mul.rbf.variance 1.67355438177 +ve
sum.mul.rbf.lengthscale 2.25937641453 +ve
sum.mul.coregion.W (3, 1) fixed
sum.mul.coregion.kappa (3,) +ve
sum.bias.variance 47.0055298343 +ve
Student_T.t_scale2 0.466869541971 +ve
Student_T.deg_free 649705.042094 +ve
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VKrhS0upwfTOa2dJv/rYdfbOjzR9WPM6l02Z2ORsdjhgEQmE0IdCN1NVEtVrM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\n3YxW2UiPa+3atVx++eXcccc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gfCffvXoSZxam7+YORPd9YhgMGuAgLye38/9fJrBaTDjt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UVbL4e/IUj1we7plcfdH4YPsUuqKv1Opf/Qwfvf9qTVnebub8L1YzXCNIkwz/uqmf0x1G9+W1aT\ntN7pf8QP1w9HbFows5dhakLOHYxPhCz5EFlCloT6ZMlHIks+RJaQJaE+WaKEJxrutPDBvh9u1zq9\nqdgah8FcVWNnwsXjnh+59pSkB2rMsx2RNOPu36ccQ27h/V+TdDXHt2VhjvWqpJHUf390FllCliSu\nT5aUFFlCliSuT5YUSCkaLD7YAGIgSwDEQJYAva0UDRYAAAAAFEHX7IMFAAAAAEVHgwUAAAAAkdBg\nAQAAAEAkNFgAAAAAEAkNFgAAAABEQoMFACgUM6s2T9hqZtPh/C4xljsTTj75hZnVzGzhFMu4a2Zr\nZnYxxpgAAOVDgwUAKJpRSV9Kkrs/dPd7kZbrkr5293+eegHut9U4mScAAG3RYAEAiua2pKmw9WrG\nzBbCFqfvzOxB2Ap1y8yWzGzFzMYlycy+Cff3H2vDWq4nwvJWzGwuLGMmLOelmf0+1FwKz6t2/qUD\nALpdf+4BAABwyIKkS+7+sDlVMHB3nw2P3XT3a+H2l2b2Wfj5VTMblrQi6dNj6oyEZVQlPZW0GB7/\nnbt/GqYmrrj7V2ZWkzQiaSPmCwUAlA9bsAAARWNHPP4sXG/oYJreuqRhSROSxszsgaT7kn4+poZL\neiRJ7n64aXoUru9LMjNbknRD0tpJXwAAoHfRYAEAiuyoZuvwz59Keubus+4+K+nBGZcrSbOSvnX3\na2o0dPMn+B0AQI9jiiAAoGjW1Ng/alqNLU1N3nL9wW13Xwz7SS2pMZXvr8fUaF3GUctekfR3M1sP\nj904zYsBAPQWc/fjnwUAQJcLDdvYWY9KaGYrkv7g7m/ijAwAUCZMEQQA9JKbZvbFaX/ZzO5KuhJx\nPACAkmELFgAAAABEwhYsAAAAAIiEBgsAAAAAIqHBAgAAAIBIaLAAAAAAIBIaLAAAAACIhAYLAAAA\nACL5H3ZKpQCwn1MBAAAAAElFTkSuQmCC\n", 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Mri4ipWzqQdv6lYZmL8tfepdDx+sxGQ3c+6XJLLx0XEzv5AohuHXe+YwaksF/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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "mc, mi = fit_and_display('141200_at')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Is a Gene Differentially Expressed?\n", "\n", "When testing whether the replicates are valid, we can reverse the question and ask whether two *different* genes are differentially expressed. Stegle et al (in a more sophisticated way than our simple analysis) show how this idea can be used to determine whether a gene has been differentially expressed. In recent work with Paul Heath and Sura Zaki Al Rashir we are combining such differential expression studies with multiple conditions giving tests to determine under which of the conditions the genes are differentially expressed.\n", "\n", "#### work funded by the BioPreDyn and RADIANT projects." ] } ], "metadata": { "kernelspec": { "display_name": "Python 2", "language": "python", "name": "python2" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", "version": "2.7.11" } }, "nbformat": 4, "nbformat_minor": 0 }