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Changeset 0:75faf9a89f5b (2018-09-14)

Next changeset 1:bcc7a4c4cc29 (2018-12-20)

Commit message:
planemo upload commit a0e968c7bd2b6f7b963baeecb08f3a39e50f52d6

added:
quantp.r
quantp.xml
test-data/exp_design_file.tabular
test-data/output.html
test-data/protein_data.tabular
test-data/transcript_data.tabular

diff -r 000000000000 -r 75faf9a89f5b quantp.r
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/quantp.r Fri Sep 14 12:22:31 2018 -0400

[

b'@@ -0,0 +1,1004 @@\n+#***************************************************************************************************************************************\n+# Functions: Start\n+#***************************************************************************************************************************************\n+\n+#===============================================================================\n+# PCA\n+#===============================================================================\n+multisample_PCA = function(df, sampleinfo_df, outfile)\n+{\n+ tempdf = df[,-1];\n+ tempcol = colnames(tempdf);\n+ tempgrp = sampleinfo_df[tempcol,2];\n+ tempdf = t(tempdf) %>% as.data.frame();\n+ tempdf[is.na(tempdf)] = 0;\n+ tempdf$Group = tempgrp;\n+ png(outfile, width = 6, height = 6, units = \'in\', res=300);\n+ # bitmap(outfile, "png16m");\n+ g = autoplot(prcomp(select(tempdf, -Group)), data = tempdf, colour = \'Group\', size=3);\n+ plot(g);\n+ dev.off();\n+}\n+\n+#===============================================================================\n+# Regression and Cook\'s distance\n+#===============================================================================\n+singlesample_regression = function(PE_TE_data,htmloutfile, append=TRUE)\n+{\n+ rownames(PE_TE_data) = PE_TE_data$PE_ID;\n+ regmodel = lm(PE_abundance~TE_abundance, data=PE_TE_data);\n+ regmodel_summary = summary(regmodel);\n+ \n+ cat("<font><h3>Linear Regression model fit between Proteome and Transcriptome data</h3></font>\\n",\n+ "<p>Assuming a linear relationship between Proteome and Transcriptome data, we here fit a linear regression model.</p>\\n",\n+ \'<table border=1 cellspacing=0 cellpadding=5 style="table-layout:auto; "> <tr bgcolor="#7a0019"><th><font color=#ffcc33>Parameter</font></th><th><font color=#ffcc33>Value</font></th></tr>\\n\',\n+ file = htmloutfile, append = TRUE);\n+ \n+ cat("<tr><td>Formula</td><td>","PE_abundance~TE_abundance","</td></tr>\\n",\n+ "<tr><td colspan=\'2\' align=\'center\'> <b>Coefficients</b></td>","</tr>\\n",\n+ "<tr><td>",names(regmodel$coefficients[1]),"</td><td>",regmodel$coefficients[1]," (Pvalue:", regmodel_summary$coefficients[1,4],")","</td></tr>\\n",\n+ "<tr><td>",names(regmodel$coefficients[2]),"</td><td>",regmodel$coefficients[2]," (Pvalue:", regmodel_summary$coefficients[2,4],")","</td></tr>\\n",\n+ "<tr><td colspan=\'2\' align=\'center\'> <b>Model parameters</b></td>","</tr>\\n",\n+ "<tr><td>Residual standard error</td><td>",regmodel_summary$sigma," (",regmodel_summary$df[2]," degree of freedom)</td></tr>\\n",\n+ "<tr><td>F-statistic</td><td>",regmodel_summary$fstatistic[1]," ( on ",regmodel_summary$fstatistic[2]," and ",regmodel_summary$fstatistic[3]," degree of freedom)</td></tr>\\n",\n+ "<tr><td>R-squared</td><td>",regmodel_summary$r.squared,"</td></tr>\\n",\n+ "<tr><td>Adjusted R-squared</td><td>",regmodel_summary$adj.r.squared,"</td></tr>\\n",\n+ file = htmloutfile, append = TRUE);\n+ \n+ cat("</table>\\n", file = htmloutfile, append = TRUE);\n+ \n+ cat(\n+ "<font color=\'#ff0000\'><h3>Regression and diagnostics plots</h3></font>\\n",\n+ file = htmloutfile, append = TRUE);\n+ \n+ outplot = paste(outdir,"/PE_TE_lm_1.png",sep="",collapse="");\n+ png(outplot, width = 10, height = 10, units = \'in\',res=300);\n+ # bitmap(outplot, "png16m");\n+ par(mfrow=c(1,1));\n+ plot(regmodel, 1, cex.lab=1.5);\n+ dev.off();\n+ \n+ outplot = paste(outdir,"/PE_TE_lm_2.png",sep="",collapse="");\n+ png(outplot,width = 10, height = 10, units = \'in\', res=300);\n+ # bitmap(outplot, "png16m");\n+ par(mfrow=c(1,1));\n+ plot(regmodel, 2, cex.lab=1.5);\n+ dev.off();\n+ \n+ outplot = paste(outdir,"/PE_TE_lm_5.png",sep="",collapse="");\n+ png(outplot, width = 10, height = 10, units = \'in\',res=300);\n+ # bitmap(outplot, "png16m");\n+ par(mfrow=c(1,1));\n+ plot(regmodel, 5, cex.lab=1.5);\n+ dev.off();\n+ \n+ cat(\'<table border=1 cellspacing=0 cellpadding=5 style="table-layout:auto; ">\', file = htmloutfile, append = TRUE);\n+ \n+ cat(\n+ \'<tr bgcolor="#7a0019"><th>\', "<'..b'3></font>\', file = htmloutfile, append = TRUE);\n+ cat(\'<table border=1 cellspacing=0 cellpadding=5 style="table-layout:auto; "> <tr bgcolor="#7a0019"><th><font color=#ffcc33>Boxplot: Transcriptome data</font></th><th><font color=#ffcc33>Boxplot: Proteome data</font></th></tr>\\n\',\n+ "<tr><td align=center>", \'<img src="Box_TE.png" width=500 height=500></td>\\n\', file = htmloutfile, append = TRUE);\n+ multisample_boxplot(TE_df, sampleinfo_df, outplot, "Yes", "Sample (log2(case/control))", "Transcript Abundance fold-change (log2)");\n+ \n+ # PE Boxplot\n+ outplot = paste(outdir,"/Box_PE.png",sep="",collape="");\n+ cat("<td align=center>", \'<img src="Box_PE.png" width=500 height=500></td></tr></table>\\n\', file = htmloutfile, append = TRUE);\n+ multisample_boxplot(PE_df, sampleinfo_df, outplot, "Yes", "Sample (log2(case/control))", "Protein Abundance fold-change(log2)");\n+ \n+ \n+ # Log Fold Data\n+ perform_Test_Volcano(TE_df_orig,PE_df_orig,TE_df, PE_df,sampleinfo_df_orig,method,correction_method,volc_with)\n+ \n+ \n+ \n+ # Print PCA\n+ \n+ cat(\'<br><br><table border=1 cellspacing=0 cellpadding=5 style="table-layout:auto; "> <tr bgcolor="#7a0019"><th><font color=#ffcc33>PCA plot: Transcriptome data</font></th><th><font color=#ffcc33>PCA plot: Proteome data</font></th></tr>\\n\',\n+ "<tr><td align=center>", \'<img src="PCA_TE_all_rep.png" width=500 height=500></td>\\n\',\n+ "<td align=center>", \'<img src="PCA_PE_all_rep.png" width=500 height=500></td></tr></table>\\n\', \n+ file = htmloutfile, append = TRUE);\n+ \n+ \n+ \n+ cat(\'<hr/><h2 id="corr_data"><font color=#ff0000>CORRELATION</font></h2>\\n\',\n+ file = htmloutfile, append = TRUE);\n+ \n+ # TE PE scatter\n+ outplot = paste(outdir,"/TE_PE_scatter.png",sep="",collape="");\n+ cat(\'<br><table border=1 cellspacing=0 cellpadding=5 style="table-layout:auto; "> <tr bgcolor="#7a0019"><th><font color=#ffcc33>Scatter plot between Proteome and Transcriptome Abundance</font></th></tr>\\n\', file = htmloutfile, append = TRUE);\n+ cat("<tr><td align=center>", \'<img src="TE_PE_scatter.png" width=800 height=800></td>\\n\', file = htmloutfile, append = TRUE);\n+ PE_TE_data = data.frame(PE_df, TE_df);\n+ colnames(PE_TE_data) = c("PE_ID","PE_abundance","TE_ID","TE_abundance");\n+ singlesample_scatter(PE_TE_data, outplot); \n+\n+ # TE PE Cor\n+ cat("<tr><td align=center>\\n", file = htmloutfile, append = TRUE);\n+ singlesample_cor(PE_TE_data, htmloutfile, append=TRUE);\n+ cat(\'<font color="red">*Note that <u>correlation</u> is <u>sensitive to outliers</u> in the data. So it is important to analyze outliers/influential observations in the data.<br> Below we use <u>Cook\\\'s distance based approach</u> to identify such influential observations.</font>\\n\',\n+ file = htmloutfile, append = TRUE);\n+ cat(\'</td></table>\',\n+ file = htmloutfile, append = TRUE);\n+ \n+ cat(\'<hr/><h2 id="regression_data"><font color=#ff0000>REGRESSION ANALYSIS</font></h2>\\n\',\n+ file = htmloutfile, append = TRUE);\n+ \n+ # TE PE Regression\n+ singlesample_regression(PE_TE_data,htmloutfile, append=TRUE);\n+ \n+ cat(\'<hr/><h2 id="cluster_data"><font color=#ff0000>CLUSTER ANALYSIS</font></h2>\\n\',\n+ file = htmloutfile, append = TRUE);\n+ \n+ #TE PE Heatmap\n+ singlesample_heatmap(PE_TE_data, htmloutfile, hm_nclust);\n+ \n+ #TE PE Clustering (kmeans)\n+ singlesample_kmeans(PE_TE_data, htmloutfile, nclust=as.numeric(numCluster))\n+ \n+ }\n+}\n+cat("<h3>Go To:</h3>\\n",\n+ "<ul>\\n",\n+ "<li><a href=#sample_dist>Sample distribution</a></li>\\n",\n+ "<li><a href=#corr_data>Correlation</a></li>\\n",\n+ "<li><a href=#regression_data>Regression analysis</a></li>\\n",\n+ "<li><a href=#inf_obs>Influential observations</a></li>\\n",\n+ "<li><a href=#cluster_data>Cluster analysis</a></li></ul>\\n",\n+ "<br><a href=#>TOP</a>",\n+ file = htmloutfile, append = TRUE);\n+cat("</body></html>\\n", file = htmloutfile, append = TRUE);\n'

diff -r 000000000000 -r 75faf9a89f5b quantp.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/quantp.xml Fri Sep 14 12:22:31 2018 -0400

[

b'@@ -0,0 +1,195 @@\n+<tool id="quantp" name="QuanTP" version="1.0.0">\n+ <description>Correlation between protein and transcript abundances</description>\n+ <requirements>\n+ <requirement type="package" version="1.10.4">r-data.table</requirement>\n+ <requirement type="package" version="3.0.1">r-gplots</requirement>\n+ <requirement type="package" version="0.7.6">r-dplyr</requirement>\n+ <requirement type="package" version="3.0.0">r-ggplot2</requirement>\n+ <requirement type="package" version="0.4.5">r-ggfortify</requirement>\n+ </requirements>\n+ <command detect_errors="exit_code"><![CDATA[\n+Rscript \'$__tool_directory__/quantp.r\' \n+ $experiment_design_option.sample_type \n+ $experiment_design_option.method_type \n+ $experiment_design_option.exp_design \n+ \'$pe_exp\' \n+ \'$te_exp\' \n+ $experiment_design_option.correction_method \n+ $cooksd_upper \n+ $nclust \n+ $hm_nclust \n+ $experiment_design_option.volcano_with \n+ \'$html_file\' \n+ \'$html_file.files_path\'\n+]]></command>\n+ <inputs>\n+ <param name="pe_exp" type="data" format="tabular" label="Input Protein Abundance File" help="Protein abundance input file"/>\n+ <param name="te_exp" type="data" format="tabular" label="Input RNA Abundance File" help="Transcript abundance input file"/>\n+ <conditional name="experiment_design_option">\n+ <param name="sample_type" type="select" label="Select data input type" help="If the input files already have fold-change values, select Log fold-change. Else, select abundances and the tool will perform the fold-change analysis">\n+ <option value="multiple" selected="True">Abundances from different conditions with or without replicates (in multiple columns)</option>\n+ <option value="logfold">Log fold-change values (or single condition abundance without replicates in single column) data</option>\n+ </param>\n+ <when value="logfold">\n+ <param name="exp_design" type="hidden" value="none" />\n+ <param name="method_type" type="hidden" value="none" />\n+ <param name="correction_method" type="hidden" value="none" />\n+ <param name="volcano_with" type="hidden" value="pval" />\n+ </when>\n+ <when value="multiple">\n+ <param name="exp_design" type="data" format="tabular" help="Please check the format of the experiment design file">\n+ <label>Experiment design File (Please see the format below)</label>\n+ </param>\n+ <param name="method_type" type="select" label="Data summarization method" help="Perform T-Test on selecting Mean; Wilcoxon Ranksum Test on selecting Median">\n+ <option value="mean" selected="True">Mean (Default)</option>\n+ <option value="median">Median</option>\n+ </param>\n+ <param name="correction_method" type="select" label="Multiple testing correction method">\n+ <option value="BH" selected="True">Benjamini and Hochberg (BH) (Default)</option>\n+ <option value="holm">Holm</option>\n+ <option value="hochberg">Hochberg</option>\n+ <option value="hommel">Hommel</option>\n+ <option value="bonferroni">Bonferroni</option>\n+ <option value="BY">Benjamini and Yekutieli (BY)</option>\n+ <option value="none">None</option>\n+ </param>\n+ <param name="volcano_with" type="select" display="radio" label="Volcano plot with p-value or adjusted p-value">\n+ <option value="pval" selected="True">P-value (Default)</option>\n+ <option value="adj_pval">Adjusted P-value</option>\n+ </param>\n+ </when>\n+ </conditional>\n+ <param name="cooksd_upper" type="integer" value="4" optional="false" >\n+ <l'..b' <param name="sample_type" value="multiple"/>\n+ <param name="method_type" value="mean"/>\n+ <param name="exp_design" value="exp_design_file.tabular" ftype="tabular" />\n+ <param name="correction_method" value="BH"/>\n+ <param name="volcano_with" value="pval"/>\n+ </conditional>\n+ <param name="pe_exp" value="protein_data.tabular" ftype="tabular" />\n+ <param name="te_exp" value="transcript_data.tabular" ftype="tabular" />\n+ <param name="cooksd_upper" value="4"/>\n+ <param name="nclust" value="4"/>\n+ <param name="hm_nclust" value="5"/>\n+ <output name="html_file">\n+ <assert_contents>\n+ <has_text text="SAMPLE DISTRIBUTION" />\n+ </assert_contents>\n+ </output>\n+ </test>\n+ </tests>\n+ <help><![CDATA[\n+\n+**What it does**\n+\n+QuanTP correlates *transcript abundance* and *protein abundance* to examine the association between them.\n+\n+It either takes in the log fold-change of abundances as input or raw abundances from different conditions where it calculates the log ratios of abundances between two conditions.\n+\n+Transcript input file can be generated from the quantitative RNA-Seq study whereas Protein input file can be generated from quantitative analysis of mass-spectrometry-based protein data.\n+\n+-----\n+\n+**Input file formats**\n+\n+**Protein data file**\n+\n+First column - Gene\n+\n+Following columns - Abundance values (or log fold-change values)\n+\n+Example of Protein input file\n+\n+====== ========= ========= ========= ========= ========= ========= ========= =========\n+Gene sample1 sample2 sample3 sample4 sample5 sample6 sample7 sample8\n+------ --------- --------- --------- --------- --------- --------- --------- ---------\n+GeneX value value value value value value value value \n+GeneY value value value value value value value value \n+GeneZ value value value value value value value value \n+====== ========= ========= ========= ========= ========= ========= ========= =========\n+\n+\n+**Transcript data file**\n+\n+First column - Gene\n+\n+Following columns - Abundance values (or log fold-change values)\n+\n+Example of Transcript input file\n+\n+====== ========= ========= ========= ========= ========= ========= ========= =========\n+Gene sample1 sample2 sample3 sample4 sample5 sample6 sample7 sample8 \n+------ --------- --------- --------- --------- --------- --------- --------- ---------\n+GeneX value value value value value value value value \n+GeneY value value value value value value value value \n+GeneZ value value value value value value value value \n+====== ========= ========= ========= ========= ========= ========= ========= =========\n+\n+\n+**Data input type**\n+\n+If data input type is abundance, experiment design file is required.\n+\n+Example of experiment design file\n+\n+======== =========\n+case groupA \n+control groupB \n+sample1 groupA \n+sample2 groupA \n+sample3 groupA \n+sample4 groupA \n+sample5 groupB \n+sample6 groupB \n+sample7 groupB \n+sample8 groupB \n+======== =========\n+\n+Note: No title/header in experiment design file and the first two lines of the experiment design must have keyword "case" and "control"\n+\n+ ]]>\n+ </help>\n+ <citations>\n+ <citation type="bibtex">\n+@misc{QuanTP: A software resource for quantitative proteo-transcriptomic comparative data analysis and informatics,\n+ author={Praveen Kumar, Priyabrata Panigrahi, James Johnson, Wanda Weber, Subina Mehta, Ray Sajulga, Caleb Easterly, Brian Crooker, Mohammad Heydarian, Krishanpal Anamika, Timothy Griffin, and Pratik Jagtap},\n+ year={2018},\n+ title={QuanTP}\n+}\n+ </citation>\n+ </citations>\n+</tool>\n'

diff -r 000000000000 -r 75faf9a89f5b test-data/exp_design_file.tabular
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/exp_design_file.tabular Fri Sep 14 12:22:31 2018 -0400

@@ -0,0 +1,6 @@
+case G1
+control G2
+D03_01 G1
+D03_02 G1
+M14_01 G2
+M14_02 G2

diff -r 000000000000 -r 75faf9a89f5b test-data/output.html
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.html Fri Sep 14 12:22:31 2018 -0400

b'@@ -0,0 +1,155 @@\n+<html><head></head><body>\n+<h1><u>QuanTP: Association between abundance ratios of transcript and protein</u></h1><hr/>\n+ <font><h3>Input data summary</h3></font>\n+ <ul>\n+ <li>Abbreviations used: PE (Proteome data) and TE (Transcriptome data) </li><br>\n+ <li>Input Proteome data dimension (Row Column): 2817 x 5 </li>\n+ <li>Input Transcriptome data dimension (Row Column): 2817 x 5 </li></ul><hr/>\n+<h3 id=table_of_content>Table of Contents:</h3>\n+ <ul>\n+ <li><a href=#sample_dist>Sample distribution</a></li>\n+ <li><a href=#corr_data>Correlation</a></li>\n+ <li><a href=#regression_data>Regression analysis</a></li>\n+ <li><a href=#inf_obs>Influential observations</a></li>\n+ <li><a href=#cluster_data>Cluster analysis</a></li></ul><hr/>\n+<h2 id="sample_dist"><font color=#ff0000>SAMPLE DISTRIBUTION</font></h2>\n+<table border=1 cellspacing=0 cellpadding=5 style="table-layout:auto; ">\n+ <tr bgcolor="#7a0019"><th><font color=#ffcc33>Boxplot: Transcriptome data</font></th><th><font color=#ffcc33>Boxplot: Proteome data</font></th></tr>\n+ <tr><td align=center> <img src="Box_TE_all_rep.png" width=500 height=500></td>\n+<td align=center> <img src="Box_PE_all_rep.png" width=500 height=500></td></tr></table>\n+<br><font color="#ff0000"><h3>Sample wise distribution (Box plot) after using mean on replicates </h3></font><table border=1 cellspacing=0 cellpadding=5 style="table-layout:auto; "> <tr bgcolor="#7a0019"><th><font color=#ffcc33>Boxplot: Transcriptome data</font></th><th><font color=#ffcc33>Boxplot: Proteome data</font></th></tr>\n+ <tr><td align=center> <img src="Box_TE_rep.png" width=500 height=500></td>\n+<td align=center> <img src="Box_PE_rep.png" width=500 height=500></td></tr></table>\n+<br><font color="#ff0000"><h3>Distribution (Box plot) of log fold change </h3></font><table border=1 cellspacing=0 cellpadding=5 style="table-layout:auto; "> <tr bgcolor="#7a0019"><th><font color=#ffcc33>Boxplot: Transcriptome data</font></th><th><font color=#ffcc33>Boxplot: Proteome data</font></th></tr>\n+ <tr><td align=center> <img src="Box_TE.png" width=500 height=500></td>\n+<td align=center> <img src="Box_PE.png" width=500 height=500></td></tr></table>\n+<br><br><font size=5><b><a href=\'PE_TE_logfold_pval.txt\' target=\'_blank\'>Download the complete fold change data here</a></b></font><br>\n+<br><table border=1 cellspacing=0 cellpadding=5 style="table-layout:auto; "> <tr bgcolor="#7a0019"><th><font color=#ffcc33>Transcript Fold-Change</font></th><th><font color=#ffcc33>Protein Fold-Change</font></th></tr>\n+<tr><td align=center> <img src="TE_volcano.png" width=600 height=600></td>\n+<td align=center> <img src="PE_volcano.png" width=600 height=600></td></tr></table><br>\n+<br><br><table border=1 cellspacing=0 cellpadding=5 style="table-layout:auto; "> <tr bgcolor="#7a0019"><th><font color=#ffcc33>PCA plot: Transcriptome data</font></th><th><font color=#ffcc33>PCA plot: Proteome data</font></th></tr>\n+ <tr><td align=center> <img src="PCA_TE_all_rep.png" width=500 height=500></td>\n+ <td align=center> <img src="PCA_PE_all_rep.png" width=500 height=500></td></tr></table>\n+<hr/><h2 id="corr_data"><font color=#ff0000>CORRELATION</font></h2>\n+<br><table border=1 cellspacing=0 cellpadding=5 style="table-layout:auto; "> <tr bgcolor="#7a0019"><th><font color=#ffcc33>Scatter plot between Proteome and Transcriptome Abundance</font></th></tr>\n+<tr><td align=center> <img src="TE_PE_scatter.png" width=800 height=800></td>\n+<tr><td align=center>\n+<table border=1 cellspacing=0 cellpadding=5 style="table-layout:auto; "> <tr bgcolor="#7a0019"><th><font color=#ffcc33>Parameter</font></th><th><font color=#ffcc33>Method 1</font></th><th><font color=#ffcc33>Method 2</font></th><th><font color=#ffcc33>Method 3</font></th></tr>\n+<tr><td>Correlation method</td><td> Pearson\'s product-moment correlation </td><td> Spearman\'s rank correlation rho </td><td> Kendall\'s rank correlation tau </td></tr>\n+ <tr><td>Correlation coefficient</td><td> 0.1173569 </td><td> 0.'..b'on </td><td> Spearman\'s rank correlation rho </td><td> Kendall\'s rank correlation tau </td></tr>\n+ <tr><td>Correlation coefficient</td><td> 0.1173569 </td><td> 0.1608612 </td><td> 0.1093701 </td></tr>\n+</table>\n+</td>\n+<td><table border=1 cellspacing=0 cellpadding=5 style="table-layout:auto; "> <tr bgcolor="#7a0019"><th><font color=#ffcc33>Parameter</font></th><th><font color=#ffcc33>Method 1</font></th><th><font color=#ffcc33>Method 2</font></th><th><font color=#ffcc33>Method 3</font></th></tr>\n+<tr><td>Correlation method</td><td> Pearson\'s product-moment correlation </td><td> Spearman\'s rank correlation rho </td><td> Kendall\'s rank correlation tau </td></tr>\n+ <tr><td>Correlation coefficient</td><td> 0.1334038 </td><td> 0.1611936 </td><td> 0.1082761 </td></tr>\n+</table></td></tr></table>\n+<br><br><font size=5><b><a href=\'PE_TE_influential_observation.txt\' target=\'_blank\'>Download the complete list of influential observations</a></b></font>     <font size=5><b><a href=\'PE_TE_non_influential_observation.txt\' target=\'_blank\'>Download the complete list (After removing influential points)</a></b></font><br>\n+ <br><font color="brown"><h4>Top 10 Influential observations (Cook\'s distance > 4 * mean Cook\'s distance)</h4></font>\n+<table border=1 cellspacing=0 cellpadding=5> <tr bgcolor="#7a0019">\n+<th><font color=#ffcc33>Gene</font></th><th><font color=#ffcc33>Protein Log Fold-Change</font></th><th><font color=#ffcc33>Transcript Log Fold-Change</font></th><th><font color=#ffcc33>Cook\'s Distance</font></th></tr>\n+<tr> <td> CATHL2 </td>\n+ <td> -1.960863 </td>\n+ <td> 4.88565 </td>\n+ <td> 0.1432189 </td></tr>\n+<tr> <td> CD177 </td>\n+ <td> -4.173263 </td>\n+ <td> 2.057499 </td>\n+ <td> 0.06826605 </td></tr>\n+<tr> <td> CATHL1 </td>\n+ <td> -0.9912973 </td>\n+ <td> 4.835209 </td>\n+ <td> 0.05767091 </td></tr>\n+<tr> <td> HP </td>\n+ <td> 2.570727 </td>\n+ <td> 3.885549 </td>\n+ <td> 0.04680496 </td></tr>\n+<tr> <td> AZU1 </td>\n+ <td> -2.226356 </td>\n+ <td> -5.561874 </td>\n+ <td> 0.03737565 </td></tr>\n+<tr> <td> ELANE </td>\n+ <td> -2.732479 </td>\n+ <td> -2.914936 </td>\n+ <td> 0.03266198 </td></tr>\n+<tr> <td> PYGM </td>\n+ <td> -0.06079228 </td>\n+ <td> 6.071712 </td>\n+ <td> 0.03242859 </td></tr>\n+<tr> <td> LTF </td>\n+ <td> -2.4294 </td>\n+ <td> 2.129742 </td>\n+ <td> 0.02725017 </td></tr>\n+<tr> <td> ATP1A2 </td>\n+ <td> 0.2871971 </td>\n+ <td> 6.446299 </td>\n+ <td> 0.01939256 </td></tr>\n+<tr> <td> C13H20orf194 </td>\n+ <td> -5.640732 </td>\n+ <td> -0.6697401 </td>\n+ <td> 0.01852927 </td></tr>\n+</table><br><br>\n+<hr/><h2 id="cluster_data"><font color=#ff0000>CLUSTER ANALYSIS</font></h2>\n+<br><table border=1 cellspacing=0 cellpadding=5 style="table-layout:auto; "> <tr bgcolor="#7a0019"><th><font color=#ffcc33>Heatmap of PE and TE abundance values (Hierarchical clustering)</font></th><th><font color=#ffcc33>Number of clusters to extract: 5 </font></th></tr>\n+<tr><td align=center colspan="2"><img src="PE_TE_heatmap.png" width=800 height=800></td></tr>\n+<tr><td colspan="2" align=center><font size=5><a href="PE_TE_hc_clusterpoints.txt" target="_blank"><b>Download the hierarchical cluster list</b></a></font></td></tr></table>\n+<br><br><table border=1 cellspacing=0 cellpadding=5 style="table-layout:auto; "> <tr bgcolor="#7a0019"><th><font color=#ffcc33>K-mean clustering</font></th><th><font color=#ffcc33>Number of clusters: 4 </font></th></tr>\n+<tr><td colspan="2" align=center><img src="PE_TE_kmeans.png" width=800 height=800></td></tr>\n+<tr><td colspan="2" align=center><font size=5><a href="PE_TE_kmeans_clusterpoints.txt" target="_blank"><b>Download the cluster list</b></a></font></td></tr></table><br><hr/>\n+<h3>Go To:</h3>\n+ <ul>\n+ <li><a href=#sample_dist>Sample distribution</a></li>\n+ <li><a href=#corr_data>Correlation</a></li>\n+ <li><a href=#regression_data>Regression analysis</a></li>\n+ <li><a href=#inf_obs>Influential observations</a></li>\n+ <li><a href=#cluster_data>Cluster analysis</a></li></ul>\n+ <br><a href=#>TOP</a></body></html>\n'

diff -r 000000000000 -r 75faf9a89f5b test-data/protein_data.tabular
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/protein_data.tabular Fri Sep 14 12:22:31 2018 -0400

b'@@ -0,0 +1,2818 @@\n+Gene\tD03_01\tD03_02\tM14_01\tM14_02\n+ELANE\t90604000.0\t100390000.0\t623380000.0\t645960000.0\n+AGL\t976501500.0\t960830000.0\t697130000.0\t719100000.0\n+AGK\t19878000.0\t16422000.0\t15565000.0\t20390000.0\n+HSPA6\t67707000.0\t176540000.0\t117020000.0\t121110000.0\n+HSPA5\t11009000000.0\t6568200000.0\t4795000000.0\t5734100000.0\n+HSPA4\t117790000.0\t30519000.0\t90678000.0\t87974000.0\n+HSPA9\t3544300000.0\t3817500000.0\t2235000000.0\t2270700000.0\n+HSPA8\t7526200000.0\t7289900000.0\t3520000000.0\t4052400000.0\n+AGA\t240460000.0\t291780000.0\t221830000.0\t173620000.0\n+LGALS3\t186500000.0\t258100000.0\t242190000.0\t301190000.0\n+CSNK2A2\t132720000.0\t155250000.0\t150050000.0\t161600000.0\n+PMM2\t1632800000.0\t1802500000.0\t1614800000.0\t1711000000.0\n+PMM1\t0.0\t10979000.0\t8686700.0\t6732400.0\n+ASS1\t18134000000.0\t18876000000.0\t12966000000.0\t12270000000.0\n+SPR\t1922200000.0\t1865500000.0\t1698600000.0\t1728400000.0\n+RNF114\t183640000.0\t174460000.0\t178010000.0\t173870000.0\n+UCHL3\t274130000.0\t282050000.0\t254500000.0\t274000000.0\n+ENSBTAG00000047256\t57543000.0\t71609000.0\t71386000.0\t61095000.0\n+ABCD3\t55147000.0\t49370000.0\t55492000.0\t45594000.0\n+SCLY\t299950000.0\t329280000.0\t324400000.0\t272070000.0\n+DHX9\t213070000.0\t112580000.0\t88925000.0\t91000000.0\n+OSGEP\t601030000.0\t575840000.0\t580200000.0\t637320000.0\n+NUP98\t2508700.0\t0.0\t6975000.0\t9160400.0\n+PPP2R2B\t29533000.0\t27090000.0\t35168000.0\t28130000.0\n+GOLIM4\t55757000.0\t13447000.0\t28969000.0\t24689000.0\n+ENSBTAG00000039928\t20107200000.0\t17840800000.0\t22329600000.0\t21414400000.0\n+OPA3\t238630000.0\t258440000.0\t236320000.0\t194580000.0\n+OPA1\t170770000.0\t88756000.0\t124230000.0\t135980000.0\n+PIK3C3\t624380.0\t0.0\t0.0\t0.0\n+GK\t79958000.0\t91689000.0\t55521000.0\t67336000.0\n+PTRH2\t630860000.0\t635300000.0\t792900000.0\t721580000.0\n+HNRNPDL\t184260000.0\t197110000.0\t180510000.0\t178040000.0\n+ENSBTAG00000024233\t6670900000.0\t7453900000.0\t5794600000.0\t6289800000.0\n+TRAPPC3\t350960000.0\t386150000.0\t288830000.0\t254040000.0\n+TRAPPC5\t110960000.0\t91402000.0\t94205000.0\t99412000.0\n+ACLY\t121870000.0\t11334000.0\t52304000.0\t57826000.0\n+CTBP2\t134900000.0\t121550000.0\t139080000.0\t127730000.0\n+ITGA9\t2480600.0\t0.0\t0.0\t0.0\n+ENSBTAG00000021558\t0.0\t0.0\t0.0\t0.0\n+HACL1\t3750000000.0\t4002800000.0\t4908400000.0\t5092300000.0\n+ITGA1\t1398200.0\t0.0\t0.0\t0.0\n+NOP2\t4928000.0\t0.0\t0.0\t0.0\n+ITGA6\t97078000.0\t42673000.0\t116280000.0\t130990000.0\n+PDCD10\t142700000.0\t124020000.0\t194810000.0\t170930000.0\n+ENSBTAG00000014423\t100010000.0\t99218000.0\t191870000.0\t184010000.0\n+EDC4\t10047000.0\t6662500.0\t0.0\t13081000.0\n+APOA4\t5577600000.0\t5684300000.0\t2510700000.0\t2632000000.0\n+APOA5\t257940000.0\t333300000.0\t197140000.0\t201230000.0\n+UFSP2\t8208200.0\t6119600.0\t0.0\t7495400.0\n+XPO1\t6101300.0\t0.0\t21163000.0\t15852000.0\n+CSDE1\t6845000.0\t10436000.0\t29616000.0\t35114000.0\n+XPO7\t1621500.0\t0.0\t13304000.0\t5299000.0\n+MRPL28\t82108000.0\t97797000.0\t62910000.0\t50735000.0\n+TIPRL\t223950000.0\t199410000.0\t192400000.0\t118190000.0\n+LSS\t346220000.0\t249770000.0\t234680000.0\t220640000.0\n+PSMG2\t66523000.0\t96697000.0\t25795000.0\t29839000.0\n+GHDC\t24907000.0\t27587000.0\t38327000.0\t43611000.0\n+COL4A2\t116880000.0\t133790000.0\t113920000.0\t117830000.0\n+COL4A1\t145000000.0\t165870000.0\t135390000.0\t135500000.0\n+MOGAT1\t23667000.0\t33273000.0\t24912000.0\t38349000.0\n+RBM12B\t2074800.0\t0.0\t2384000.0\t3078100.0\n+GART\t497380000.0\t153590000.0\t363030000.0\t301340000.0\n+GARS\t14525000.0\t0.0\t35874000.0\t22116000.0\n+PSMD14\t416870000.0\t577850000.0\t409550000.0\t320620000.0\n+ATAD1\t429390000.0\t455220000.0\t383550000.0\t484670000.0\n+PSMD10\t52335000.0\t25236000.0\t32444000.0\t40355000.0\n+PSMD13\t1450700000.0\t1441200000.0\t1525200000.0\t1463400000.0\n+PSMD12\t16339000.0\t14892000.0\t22908000.0\t29622000.0\n+ENSBTAG00000039321\t939690.0\t0.0\t0.0\t9768400.0\n+FTCD\t2776600000.0\t2757000000.0\t3259800000.0\t3388300000.0\n+GIT1\t1902600.0\t0.0\t1368700.0\t0.0\n+SERBP1\t70643000.0\t58520000.0\t63639000.0\t60842000.0\n+PPP4C\t40084000.0\t147770000.0\t127090000.0\t154860000.0\n+OCRL\t2204200.0\t0.0\t2652100.0\t0.0\n+GANAB\t1342100000.0\t362290000.0\t592930000.0\t651410000.0\n+NUP133\t506790.0\t0.0\t3742200.0\t4045600.0\n+LRPAP1\t91487000.0\t8423000'..b'\t195260000.0\t191020000.0\t126030000.0\n+FMO1\t5945400000.0\t6490600000.0\t9987500000.0\t10148000000.0\n+ENSBTAG00000038549\t232750000.0\t249300000.0\t373940000.0\t424670000.0\n+RCC2\t27806000.0\t28080000.0\t16173000.0\t18826000.0\n+PBLD\t3249700000.0\t3513100000.0\t4686300000.0\t4380100000.0\n+EEF1B2\t562230000.0\t481700000.0\t667050000.0\t653720000.0\n+ERP44\t1348000000.0\t1498600000.0\t1297900000.0\t1316400000.0\n+GCAT\t5382400000.0\t4961300000.0\t5530800000.0\t6278300000.0\n+STAU1\t29957000.0\t37825000.0\t31143000.0\t28898000.0\n+FAAH\t17439000.0\t9643300.0\t23832000.0\t14821000.0\n+VPS26C\t113060000.0\t116510000.0\t122570000.0\t133220000.0\n+PSPH\t407370000.0\t442680000.0\t374170000.0\t435570000.0\n+UGT1A1\t1518800000.0\t1368130000.0\t1768610000.0\t1982390000.0\n+ENSBTAG00000002943\t108960000.0\t116710000.0\t66086000.0\t62555000.0\n+PGPEP1\t318030000.0\t246580000.0\t315110000.0\t345340000.0\n+GLUD1\t29655000000.0\t29556000000.0\t31977000000.0\t29422000000.0\n+ENSBTAG00000037613\t79423000.0\t55485000.0\t131260000.0\t149400000.0\n+TIMM29\t105770000.0\t93994000.0\t102570000.0\t136000000.0\n+HSP90AA1\t5334700000.0\t1532400000.0\t1907700000.0\t2031200000.0\n+TIMM23\t112960000.0\t93899000.0\t151110000.0\t108220000.0\n+TIMM22\t0.0\t0.0\t0.0\t0.0\n+TIMM21\t64127000.0\t57016000.0\t38849000.0\t31862000.0\n+KARS\t115320000.0\t99866000.0\t98437000.0\t106740000.0\n+HP1BP3\t18219000.0\t13844000.0\t33875000.0\t30816000.0\n+NDUFS8\t534330000.0\t610750000.0\t610280000.0\t639950000.0\n+CYP2D14\t4334900000.0\t3897300000.0\t5847700000.0\t7050300000.0\n+TXNDC11\t2247200.0\t0.0\t0.0\t0.0\n+CD58\t23693000.0\t25817000.0\t72580000.0\t44734000.0\n+SCP2\t5739600000.0\t5868200000.0\t6372300000.0\t6054700000.0\n+MSN\t142050000.0\t31677000.0\t88961000.0\t92443000.0\n+ZNF326\t5418500.0\t0.0\t20543000.0\t21723000.0\n+CACYBP\t1195400000.0\t1393100000.0\t1200600000.0\t913130000.0\n+PDE2A\t2195700.0\t0.0\t1515100.0\t0.0\n+OPLAH\t65110000.0\t8258800.0\t59809000.0\t82824000.0\n+SEC31A\t352840000.0\t253140000.0\t496690000.0\t422670000.0\n+PRRC1\t173280000.0\t144380000.0\t105560000.0\t97495000.0\n+RAB35\t184150000.0\t210390000.0\t210900000.0\t146690000.0\n+SRP54\t16870000.0\t0.0\t17183000.0\t0.0\n+RAB32\t199490000.0\t188260000.0\t351400000.0\t358680000.0\n+CAND1\t143430000.0\t0.0\t113590000.0\t111100000.0\n+PRPS1\t653600000.0\t756410000.0\t811960000.0\t707820000.0\n+DAO\t333390000.0\t272980000.0\t483960000.0\t495640000.0\n+TATDN1\t100810000.0\t103650000.0\t152670000.0\t202680000.0\n+ENSBTAG00000037509\t3239100000.0\t3031800000.0\t5003900000.0\t4721000000.0\n+RPIA\t529880000.0\t493570000.0\t486610000.0\t396180000.0\n+TTLL12\t137580000.0\t31001000.0\t102560000.0\t151130000.0\n+LDHD\t30163000.0\t23224000.0\t57165000.0\t30997000.0\n+GMPR2\t1031600000.0\t1196000000.0\t1168800000.0\t1186300000.0\n+LDHA\t14870000000.0\t13195000000.0\t7208500000.0\t6815000000.0\n+LDHB\t90843000000.0\t88904000000.0\t60403000000.0\t58145000000.0\n+LDHC\t536100000.0\t426860000.0\t448290000.0\t374210000.0\n+LONP2\t43884000.0\t15621000.0\t38450000.0\t34587000.0\n+PLS3\t741000000.0\t726080000.0\t702790000.0\t743600000.0\n+LONP1\t553770000.0\t100790000.0\t301640000.0\t541030000.0\n+PRPS1L1\t14452000.0\t143990000.0\t204130000.0\t173310000.0\n+PDIA6\t5536300000.0\t5153100000.0\t5742700000.0\t5418200000.0\n+PDIA5\t287100000.0\t277620000.0\t269670000.0\t311580000.0\n+PDIA4\t3752300000.0\t1290600000.0\t1720300000.0\t1680700000.0\n+PDIA3\t11361000000.0\t11404000000.0\t10557000000.0\t10780000000.0\n+GAPDHS\t0.0\t27573000.0\t0.0\t10917000.0\n+CFL2\t273520000.0\t244060000.0\t155080000.0\t116930000.0\n+CFL1\t2096000000.0\t1982600000.0\t1271000000.0\t1574900000.0\n+PLAA\t21632000.0\t30059000.0\t23076000.0\t24565000.0\n+BICD2\t588990.0\t0.0\t0.0\t0.0\n+SEC22B\t702980000.0\t952600000.0\t1044700000.0\t1106500000.0\n+NFIA\t72864000.0\t84889000.0\t132520000.0\t107650000.0\n+CD163\t11492000.0\t0.0\t11306000.0\t5193400.0\n+AARS\t146460000.0\t9450400.0\t61691000.0\t59180000.0\n+PDCD6IP\t385510000.0\t34680000.0\t144850000.0\t133720000.0\n+TSGA10\t10537000.0\t12086000.0\t8208100.0\t0.0\n+DNM1L\t11295000.0\t18871000.0\t21188000.0\t19447000.0\n+SERPINH1\t65738000.0\t86493000.0\t87575000.0\t75870000.0\n+FOLR3\t71727000.0\t76916000.0\t40142000.0\t41058000.0\n+C5orf51\t101150000.0\t94942000.0\t112990000.0\t90720000.0\n+GSTK1\t3823200000.0\t3929400000.0\t4085200000.0\t4575800000.0\n'

diff -r 000000000000 -r 75faf9a89f5b test-data/transcript_data.tabular
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/transcript_data.tabular Fri Sep 14 12:22:31 2018 -0400

b'@@ -0,0 +1,2818 @@\n+Gene\tD03_01\tD03_02\tM14_01\tM14_02\n+ELANE\t-0.08223053805901\t0.128367421476871\t0.168575604288361\t0.179386061121957\n+AGL\t18.3503026568495\t18.3971714903452\t28.8550772364392\t28.2897976837947\n+AGK\t4.96373192231441\t4.0307358661387\t4.69732878268058\t5.64327232883133\n+HSPA6\t0.350288503153011\t0.592013587104232\t0.612568173305459\t0.833794197245084\n+HSPA5\t413.409614153405\t438.011930274678\t197.673685843884\t193.727515486021\n+HSPA4\t14.8468997976502\t15.3061633055397\t15.275973226593\t14.7835817685183\n+HSPA9\t170.253077768686\t169.323500684362\t159.978594056721\t161.35877481037\n+HSPA8\t486.867209766023\t498.041303389437\t352.185123018411\t340.356699934716\n+AGA\t55.2930712045865\t50.7686596245107\t69.9129100715734\t66.07384169934\n+LGALS3\t12.3566659422422\t12.6797640900226\t18.7284481408449\t16.497115341329\n+CSNK2A2\t20.6258110499688\t20.054472820524\t18.5817134405737\t18.3292680140834\n+PMM2\t21.8385112586243\t23.0035148281517\t16.003600132562\t17.2109074501839\n+PMM1\t8.10344421010251\t6.45300943797042\t5.29673056867481\t5.29511229568809\n+ASS1\t1516.70059430521\t1464.12181445199\t987.76849371654\t994.644000920779\n+SPR\t29.8024212677962\t31.4255886777817\t31.79677566883\t28.6670221909796\n+RNF114\t33.1294000243847\t33.6664789344251\t28.9252501819995\t29.2816301523686\n+UCHL3\t24.423075481539\t27.4024225580356\t29.922955743965\t26.0349789575326\n+ENSBTAG00000047256\t0.198684163979848\t0.326976011762912\t0.0965464670861903\t0.195629128584535\n+ABCD3\t58.7883234930997\t65.4050144271272\t44.0781156389721\t45.9473853318538\n+SCLY\t18.3455097325074\t12.0439548297371\t14.5431284057665\t13.4342441387722\n+DHX9\t32.2266699445344\t36.0820538117998\t35.4491208799006\t35.8446454974175\n+OSGEP\t29.0980770472159\t32.8130489058944\t28.7841249063531\t29.9202928144102\n+NUP98\t21.4830493303323\t21.235967445222\t20.6724652583012\t22.2449776146426\n+PPP2R2B\t31.8301859398506\t30.1268425510797\t23.5899320354255\t24.1446221529343\n+GOLIM4\t77.5784923330104\t79.4625370538813\t112.276390607867\t104.067050552795\n+ENSBTAG00000039928\t359.614982869772\t382.125322623553\t543.941055328692\t546.030125904376\n+OPA3\t5.18347064997793\t4.15589059496056\t4.03566324685585\t3.86302350820354\n+OPA1\t17.0182215598298\t16.1769424590617\t14.3846256512375\t14.6461260137112\n+PIK3C3\t9.84397565598685\t8.70006988836737\t13.5221256093077\t10.8636519932476\n+GK\t65.3713999987646\t68.7043984462497\t24.7873549302085\t25.9121453607769\n+PTRH2\t17.909813910486\t11.7471606497093\t10.9263216383985\t12.0202004570597\n+HNRNPDL\t37.5925704923559\t41.1578984184042\t54.6425179347757\t52.9859134623444\n+ENSBTAG00000024233\t37.7416967628295\t39.5317543165011\t38.5879336019462\t39.9028585669302\n+TRAPPC3\t17.0068732811101\t16.3667538068817\t15.7092710313949\t15.4243816805198\n+TRAPPC5\t45.0403443110014\t42.0513255117671\t28.9286451423378\t32.7199255117285\n+ACLY\t13.4740474442297\t14.3387262055932\t9.58029287059529\t10.3337981947598\n+CTBP2\t5.99360085192578\t4.51762221965351\t4.98093076698102\t6.42950200799512\n+ITGA9\t17.6306543365399\t17.8886530469848\t22.7476079210683\t19.8507879088077\n+ENSBTAG00000021558\t21.1194017135072\t17.7807242658146\t20.1526593853834\t18.2217376654255\n+HACL1\t246.657620535078\t256.567529495172\t229.415834596451\t220.138080113882\n+ITGA1\t9.29786949411024\t9.76396771663312\t13.5013428589913\t14.8294210742118\n+NOP2\t6.80838573089712\t6.89524552209448\t6.72211107944166\t6.36046866759143\n+ITGA6\t11.8735075257508\t12.6555131238251\t15.482031234154\t15.5906619691222\n+PDCD10\t18.7315219469136\t22.601547803977\t21.2323631686951\t23.5166048769705\n+ENSBTAG00000014423\t145.95935840011\t143.533614530968\t183.076474422877\t181.551319884355\n+EDC4\t5.52923753091842\t5.7877027035443\t5.23171974237195\t5.96904629810924\n+APOA4\t1001.67305558535\t942.744279140933\t107.00083069641\t106.440618749974\n+APOA5\t1029.86419861909\t979.325280504821\t674.842850735208\t668.048257430335\n+UFSP2\t16.2749903128682\t20.256738769108\t18.7220238728349\t15.9515918998196\n+XPO1\t16.485245004257\t16.8668226905226\t18.4411687253671\t18.2090074546333\n+CSDE1\t88.2990636083208\t94.874140787585\t111.6583797805\t112.40205326067\n+XPO7\t15.7401949501504\t14.2091535237298\t17.7515728413077\t18.037145679691\n+MR'..b'7741109146881\n+KARS\t54.2791009534698\t52.7908967916207\t67.7231516102737\t67.5815708119999\n+HP1BP3\t29.3421095840681\t31.39238753324\t33.7829527675812\t32.7847645169075\n+NDUFS8\t85.4156300221413\t91.7853322351507\t65.392093459396\t61.6781463892882\n+CYP2D14\t231.360921414891\t224.485267054532\t456.577628032366\t448.65397703679\n+TXNDC11\t51.6403424117011\t51.0785155914478\t36.8772113020138\t37.7219423903237\n+CD58\t22.8671692478851\t25.164892363039\t25.7169492114737\t24.1581392883673\n+SCP2\t749.564202612591\t777.679865805852\t932.056096360398\t939.928108070764\n+MSN\t14.8468265774399\t18.6138096199231\t21.6626739228865\t21.3568084413381\n+ZNF326\t17.7799256975569\t15.6250344604187\t18.3714769148998\t18.8137140847393\n+CACYBP\t65.8511268882502\t67.8944752372627\t52.7753585597001\t60.9440250551207\n+PDE2A\t12.1014198230228\t10.126228483765\t12.4896304121948\t9.95500686142616\n+OPLAH\t11.7527157254726\t9.82513795202479\t5.45271711808034\t6.05224514488442\n+SEC31A\t55.4599343957457\t58.5404301901295\t58.8760181715344\t60.7197082614718\n+PRRC1\t34.7463089404113\t32.2595374347583\t27.6716014035645\t30.7583958831148\n+RAB35\t7.82839916809587\t8.0124938651858\t8.0771538438553\t8.58774636109239\n+SRP54\t26.9210223365744\t31.7450878893208\t31.7787240409449\t31.42668406125\n+RAB32\t142.550735319666\t134.51170785237\t117.39958831372\t115.689748377378\n+CAND1\t12.6044607008631\t14.5021655863634\t15.2072452439481\t14.6914434731307\n+PRPS1\t15.3347060001018\t15.2261635475863\t15.8085120424699\t14.9796706811849\n+DAO\t50.3961515965993\t41.4898908105392\t77.8295602693701\t77.9014073714062\n+TATDN1\t28.3902774962365\t29.2063037345338\t40.062345321928\t38.8554011671924\n+ENSBTAG00000037509\t153.974244178864\t168.577857027868\t118.59223268085\t119.688275843892\n+RPIA\t10.0411202069523\t7.71295440633761\t8.06876082077743\t7.9312262952526\n+TTLL12\t26.3146835863755\t23.400308321264\t24.8959310699421\t23.8929300367068\n+LDHD\t13.3865059324636\t12.7769732843129\t16.0981763399116\t16.158255124931\n+GMPR2\t61.5603561075099\t52.7488327338009\t46.6696736465609\t46.7349152524274\n+LDHA\t207.730032556293\t226.891741973915\t52.7798443855118\t53.0922016798784\n+LDHB\t1213.63815105495\t1294.32612194355\t407.184967798351\t410.717652900092\n+LDHC\t0.996700003910787\t1.4243441795977\t0.367575854627836\t0.529836482163856\n+LONP2\t104.723442540721\t106.230729202829\t113.693254984474\t116.563293627589\n+PLS3\t56.7198089183436\t62.5935429696212\t54.6704613566612\t54.8233621601003\n+LONP1\t35.0285838875834\t35.3617280286151\t29.2954355019332\t32.2547575935306\n+PRPS1L1\t-0.0758996600312405\t0.135819323886117\t-0.00624862361024775\t0.00569716975406065\n+PDIA6\t237.078629510045\t246.02532052621\t161.475583919526\t161.739154992676\n+PDIA5\t25.0597837080607\t28.3971220939429\t41.715172486751\t39.338047316991\n+PDIA4\t211.873913148269\t210.001936921539\t145.23112104313\t147.050443090863\n+PDIA3\t338.000109411079\t361.355970968745\t254.175745803677\t263.613526088518\n+GAPDHS\t4.02245035382783\t3.92129771588966\t5.37370796946667\t3.21280136749778\n+CFL2\t16.4395278148457\t16.6215740674699\t11.4464590162857\t14.0380871787687\n+CFL1\t270.858978945402\t277.97105818897\t251.876578742101\t259.003824894279\n+PLAA\t16.1144856376278\t15.9790411228606\t14.0881689734665\t17.6164371479456\n+BICD2\t8.08825997009739\t8.13016509366486\t7.54569660889039\t8.09658275324354\n+SEC22B\t28.0158406759932\t26.2168927410539\t25.8085478130071\t26.2476955958624\n+NFIA\t18.7998060312645\t20.6019630622779\t25.8027529792118\t24.0930147370757\n+CD163\t41.2947020425552\t45.7036852574451\t72.9594414051051\t75.7918900293897\n+AARS\t34.2338462472451\t28.8187366028439\t28.2737262835897\t29.253852156971\n+PDCD6IP\t47.5366726918095\t49.4878158869482\t49.3569707972503\t51.6081599918002\n+TSGA10\t0.532544422811476\t0.549561083730723\t0.808442535970308\t0.993907565460829\n+DNM1L\t10.9793186842086\t11.8429623497427\t10.0686886407995\t10.7556465831498\n+SERPINH1\t15.3198304548624\t15.9048127634568\t8.28307047703207\t9.71105820398736\n+FOLR3\t138.428905969161\t116.281636988597\t85.8755941382458\t89.4439500612999\n+C5orf51\t17.2935605353597\t15.0249063894766\t19.5560379723125\t22.1981123516811\n+GSTK1\t217.176269127719\t211.304802899312\t239.829423960609\t229.9821520916\n'