| Previous changeset 1:80cf607159ae (2018-02-17) Next changeset 3:f259c29b3832 (2018-04-19) |
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Commit message:
planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/mageck commit 49e456dda49db1f52fc876f406a10273a408b1a2 |
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modified:
mageck_macros.xml test-data/out.count.bam.txt test-data/out.count.fastq.txt test-data/out.count.log.txt test-data/out.countsummary.pdf test-data/out.countsummary.txt test-data/out.mle.log.txt test-data/out.test.R test-data/out.test.log.txt test-data/out.test.normalized.txt test-data/test1.fastq.gz |
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added:
test-data/in.test.sample.txt test-data/out.count.R test-data/out.count.Rnw test-data/out.count.txt test-data/out.count_multi.txt test-data/out.countsummary_multi.pdf test-data/out.normcounts.txt test-data/out.test.plots.pdf test-data/out.test.report.pdf test-data/output.count_normalized.txt test-data/output_countsummary.Rnw test-data/output_summary.Rnw test-data/test2.fastq.gz |
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removed:
test-data/out.test.pdf |
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| diff -r 80cf607159ae -r 82a180e6b582 mageck_macros.xml --- a/mageck_macros.xml Sat Feb 17 10:41:13 2018 -0500 +++ b/mageck_macros.xml Wed Apr 04 11:03:05 2018 -0400 |
| [ |
| @@ -1,27 +1,34 @@ <?xml version="1.0"?> <macros> + <token name="@VERSION@">0.5.7</token> + <xml name="requirements"> <requirements> <requirement type="package" version="@VERSION@">mageck</requirement> - <!-- needed for pdf report outputs --> + <requirement type="package" version="1.14.2">numpy</requirement> <requirement type="package" version="3.0.1">r-gplots</requirement> <requirement type="package" version="1.8_2">r-xtable</requirement> <yield/> </requirements> </xml> + <xml name="version"> - <version_command>mageck -v </version_command> + <version_command><![CDATA[ + echo $(mageck -v )", numpy version" $([python -c "import numpy; numpy.version.version"])", gplots version" $(R --vanilla --slave -e "library(gplots); cat(sessionInfo()\$otherPkgs\$gplots\$Version)" 2> /dev/null | grep -v -i "WARNING: ")", xtable version" $(R --vanilla --slave -e "library(xtable); cat(sessionInfo()\$otherPkgs\$xtable\$Version)" 2> /dev/null | grep -v -i "WARNING: ") + ]]></version_command> </xml> + + <xml name="sort_criteria"> + <param name="sort_criteria" argument="--sort-criteria" type="select" optional="true" label="Sorting criteria"> + <option value="neg" selected="True">Negative selection</option> + <option value="pos">positive selection</option> + </param> + </xml> + <xml name="citations"> <citations> <citation type="doi">10.1186/s13059-014-0554-4</citation> </citations> </xml> - <xml name="sort_criteria"> - <param name="sort_criteria" argument="--sort-criteria" type="select" label="Sorting criteria"> - <option value="neg" selected="True">Negative selection</option> - <option value="pos">positive selection</option> - </param> - </xml> </macros> |
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| diff -r 80cf607159ae -r 82a180e6b582 test-data/in.test.sample.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/in.test.sample.txt Wed Apr 04 11:03:05 2018 -0400 |
| b |
| b'@@ -0,0 +1,1000 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|
| b |
| diff -r 80cf607159ae -r 82a180e6b582 test-data/out.count.R --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/out.count.R Wed Apr 04 11:03:05 2018 -0400 |
| b |
| @@ -0,0 +1,5 @@ +Sweave("output_countsummary.Rnw"); +library(tools); + +texi2dvi("output_countsummary.tex",pdf=TRUE); + |
| b |
| diff -r 80cf607159ae -r 82a180e6b582 test-data/out.count.Rnw --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/out.count.Rnw Wed Apr 04 11:03:05 2018 -0400 |
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| @@ -0,0 +1,237 @@ +% This is a template file for Sweave used in MAGeCK +% Author: Wei Li, Shirley Liu lab +% Do not modify lines beginning with "#__". +\documentclass{article} + +\usepackage{amsmath} +\usepackage{amscd} +\usepackage[tableposition=top]{caption} +\usepackage{ifthen} +\usepackage{fullpage} +\usepackage[utf8]{inputenc} +% \usepackage{longtable} + +\begin{document} +\setkeys{Gin}{width=0.9\textwidth} + +\title{MAGeCK Count Report} +\author{Wei Li} + +\maketitle + + +\tableofcontents + +\section{Summary} + +%Function definition +<<label=funcdef,include=FALSE,echo=FALSE>>= +genreporttable<-function(filelist,labellist,reads,mappedreads){ + xtb=data.frame(Label=labellist,Reads=reads,MappedReads=mappedreads,MappedPercentage=mappedreads/reads); + colnames(xtb)=c("Label","Reads","Mapped","Percentage"); + return (xtb); +} +genreporttable2<-function(filelist,labellist,sgrnas,zerocounts,gini){ + xtb=data.frame(Label=labellist,TotalsgRNAs=sgrnas,ZeroCounts=zerocounts,GiniIndex=gini); + colnames(xtb)=c("Label","TotalsgRNA","ZeroCounts","GiniIndex"); + return (xtb); +} +genreporttable3<-function(filelist,labellist){ + xtb=data.frame(File=filelist,Label=labellist); + colnames(xtb)=c("File","Label"); + return (xtb); +} + + +colors=c( "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#A65628", "#F781BF", + "#999999", "#66C2A5", "#FC8D62", "#8DA0CB", "#E78AC3", "#A6D854", "#FFD92F", "#E5C494", "#B3B3B3", + "#8DD3C7", "#FFFFB3", "#BEBADA", "#FB8072", "#80B1D3", "#FDB462", "#B3DE69", "#FCCDE5", + "#D9D9D9", "#BC80BD", "#CCEBC5", "#FFED6F"); + + + +genboxplot<-function(filename,...){ + #slmed=read.table(filename,header=T) + slmed=read.table(filename,header=T) + slmat=as.matrix(slmed[,c(-1,-2)]) + slmat_log=log2(slmat+1) + + boxplot(slmat_log,pch='.',las=2,ylab='log2(read counts)',cex.axis=0.8,...) +} + + +genhistplot<-function(filename,isfile=T,...){ + if(isfile){ + slmed=read.table(filename,header=T) + }else{ + slmed=filename; + } + tabsmat=as.matrix(log2(slmed[,c(-1,-2)]+1)) + colnames(tabsmat)=colnames(slmed)[c(-1,-2)] + samplecol=colors[((1:ncol(tabsmat)) %% length(colors)) ] + if(ncol(tabsmat)>=1){ + histlist=lapply(1:ncol(tabsmat),function(X){ return (hist(tabsmat[,X],plot=F,breaks=40)) }) + xrange=range(unlist(lapply(histlist,function(X){X$mids}))) + yrange=range(unlist(lapply(histlist,function(X){X$counts}))) + hst1=histlist[[1]] + plot(hst1$mids,hst1$counts,type='b',pch=20,xlim=c(0,xrange[2]*1.2),ylim=c(0,yrange[2]*1.2),xlab='log2(counts)',ylab='Frequency',main='Distribution of read counts',col = samplecol[1], ... ) + } + if(ncol(tabsmat)>=2){ + for(i in 2:ncol(tabsmat)){ + hstn=histlist[[i]] + lines(hstn$mids,hstn$counts,type='b',pch=20,col=samplecol[i]) + } + } + legend('topright',colnames(tabsmat),pch=20,lwd=1,col=samplecol) +} + + + +genclustering<-function(filename,...){ + #slmed=read.table(filename,header=T) + slmed=read.table(filename,header=T) + slmat=as.matrix(slmed[,c(-1,-2)]) + slmat_log=log2(slmat+1) + + result=tryCatch({ + library(gplots); + heatmap.2(cor(slmat_log),trace = 'none',density.info = 'none',cexRow = 0.8,cexCol = 0.8,offsetRow = -0.2,offsetCol = -0.2) + }, error=function(e){ + heatmap(cor(slmat_log),scale='none',cexRow = 0.8,cexCol = 0.8,cex.axis=0.8,...) + }); +} + +ctfit_tx=0; + + +panel.plot<-function(x,y,textnames=names(x),...){ + par(new=TRUE) + m<-cbind(x,y) + plot(m,pch=20,xlim = range(x)*1.1,ylim=range(y)*1.1,...) + text(x,y,textnames,...) +} + + +genpcaplot<-function(filename,...){ + #slmed=read.table(filename,header=T) + slmed=read.table(filename,header=T) + slmat=as.matrix(slmed[,c(-1,-2)]) + slmat_log=log2(slmat+1) + ctfit_tx<<-prcomp(t(slmat_log),center=TRUE) + + # par(mfrow=c(2,1)); + samplecol=colors[((1:ncol(slmat)) %% length(colors)) ] + # first 2 PCA + #plot(ctfit_tx$x[,1],ctfit_tx$x[,2],xlab='PC1',ylab='PC2',main='First 2 PCs',col=samplecol,xlim=1.1*range(ctfit_tx$x[,1]),ylim=1.1*range(ctfit_tx$x[,2])); + #text(ctfit_tx$x[,1],ctfit_tx$x[,2],rownames(ctfit_tx$x),col=samplecol); + # par(mfrow=c(1,1)); + if(length(samplecol)>2){ + pairs(ctfit_tx$x[,1:3],panel=panel.plot,textnames=rownames(ctfit_tx$x),main='First 3 principle components',col=samplecol) + }else{ + if(length(samplecol)>1){ + pairs(ctfit_tx$x[,1:2],panel=panel.plot,textnames=rownames(ctfit_tx$x),main='First 2 principle components',col=samplecol) + } + } + + +} + +genpcavar<-function(){ + # % variance + varpca=ctfit_tx$sdev^2 + varpca=varpca/sum(varpca)*100; + if(length(varpca)>10){ + varpca=varpca[1:10]; + } + plot(varpca,type='b',lwd=2,pch=20,xlab='PCs',ylab='% Variance explained'); +} + +@ + +%__FILE_SUMMARY__ + +The statistics of comparisons are listed in Table 1 and Table 2. +The corresponding fastq files in each row are listed in Table 3. + +<<label=tab1,echo=FALSE,results=tex>>= +library(xtable) +filelist=c("input_0.gz"); +labellist=c("test1_fastq_gz"); +reads=c(2500); +mappedreads=c(1453); +totalsgrnas=c(2550); +zerocounts=c(1276); +giniindex=c(0.5266899931488773); + +cptable=genreporttable(filelist,labellist,reads,mappedreads); +print(xtable(cptable, caption = "Summary of comparisons", label = "tab:one", + digits = c(0, 0, 0, 0,2), + align=c('c', 'c','c', 'c', 'c'), + table.placement = "tbp", + caption.placement = "top")) +@ + +<<label=tab2,echo=FALSE,results=tex>>= +library(xtable) +cptable=genreporttable2(filelist,labellist,totalsgrnas,zerocounts,giniindex); +print(xtable(cptable, caption = "Summary of comparisons", label = "tab:two", + digits = c(0, 0,0, 0,2), + align=c('c', 'c','c', 'c', 'c'), + table.placement = "tbp", + caption.placement = "top")) +@ + + + + + +<<label=tab3,echo=FALSE,results=tex>>= +library(xtable) +cptable=genreporttable3(filelist,labellist); +print(xtable(cptable, caption = "Summary of samples", label = "tab:three", + digits = c(0,0, 0), + align=c('c', 'p{9cm}', 'c'), + table.placement = "tbp", + caption.placement = "top")) +@ + + + + +The meanings of the columns are as follows. + +\begin{itemize} +\item \textbf{Row}: The row number in the table; +\item \textbf{File}: The filename of fastq file; +\item \textbf{Label}: Assigned label; +\item \textbf{Reads}: The total read count in the fastq file; +\item \textbf{Mapped}: Reads that can be mapped to gRNA library; +\item \textbf{Percentage}: The percentage of mapped reads; +\item \textbf{TotalsgRNAs}: The number of sgRNAs in the library; +\item \textbf{ZeroCounts}: The number of sgRNA with 0 read counts; +\item \textbf{GiniIndex}: The Gini Index of the read count distribution. Gini index can be used to measure the evenness of the read counts, and a smaller value means a more even distribution of the read counts. +\end{itemize} + + + +\newpage\section{Normalized read count distribution of all samples} +The following figure shows the distribution of median-normalized read counts in all samples. + + +<<fig=TRUE,echo=FALSE,width=4.5,height=4.5>>= +genboxplot("output.count_normalized.txt"); +@ + +The following figure shows the histogram of median-normalized read counts in all samples. + + +<<fig=TRUE,echo=FALSE,width=4.5,height=4.5>>= +genhistplot("output.count_normalized.txt"); +@ + +%__INDIVIDUAL_PAGE__ + + + +\end{document} + |
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| diff -r 80cf607159ae -r 82a180e6b582 test-data/out.count.bam.txt --- a/test-data/out.count.bam.txt Sat Feb 17 10:41:13 2018 -0500 +++ b/test-data/out.count.bam.txt Wed Apr 04 11:03:05 2018 -0400 |
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| @@ -1,4 +1,4 @@ -sgRNA Gene test1.bam +sgRNA Gene test1_bam s_10007 CCNA1 0 s_10008 CCNA1 0 s_10027 CCNC 0 |
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| diff -r 80cf607159ae -r 82a180e6b582 test-data/out.count.fastq.txt --- a/test-data/out.count.fastq.txt Sat Feb 17 10:41:13 2018 -0500 +++ b/test-data/out.count.fastq.txt Wed Apr 04 11:03:05 2018 -0400 |
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| @@ -1,4 +1,4 @@ -sgRNA Gene test1.fastq.gz +sgRNA Gene test1_fastq_gz s_47512 RNF111 1 s_24835 HCFC1R1 1 s_14784 CYP4B1 4 |
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| diff -r 80cf607159ae -r 82a180e6b582 test-data/out.count.log.txt --- a/test-data/out.count.log.txt Sat Feb 17 10:41:13 2018 -0500 +++ b/test-data/out.count.log.txt Wed Apr 04 11:03:05 2018 -0400 |
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| @@ -1,46 +1,43 @@ -INFO @ Wed, 14 Feb 2018 01:52:58: Parameters: /home/maria/miniconda3/envs/mulled-v1-0142cfe25b04f0c1d6899e250fb2f311b2d84778259938a0f6bd1d2ee743fa71/bin/mageck count -l /tmp/tmpqZ84Xc/files/000/dataset_7.dat --fastq input.gz -n output --pdf-report --keep-tmp --unmapped-to-file --norm-method median --sgrna-len 20 -INFO @ Wed, 14 Feb 2018 01:52:58: Welcome to MAGeCK v0.5.7. Command: count -INFO @ Wed, 14 Feb 2018 01:52:58: Loading 2550 predefined sgRNAs. -WARNING @ Wed, 14 Feb 2018 01:52:58: There are 0 sgRNAs with duplicated sequences. -INFO @ Wed, 14 Feb 2018 01:52:58: Parsing FASTQ file input.gz... -INFO @ Wed, 14 Feb 2018 01:52:58: Determining the trim-5 length of FASTQ file input.gz... -INFO @ Wed, 14 Feb 2018 01:52:58: Possible gRNA lengths:20 -INFO @ Wed, 14 Feb 2018 01:52:58: Processing 0M reads ... -INFO @ Wed, 14 Feb 2018 01:52:58: Read length:30 -INFO @ Wed, 14 Feb 2018 01:52:58: Total tested reads: 2500, mapped: 1453(0.5812) -INFO @ Wed, 14 Feb 2018 01:52:58: --trim-5 test data: (trim_length reads fraction) -INFO @ Wed, 14 Feb 2018 01:52:58: 0 1453 1.0 -INFO @ Wed, 14 Feb 2018 01:52:58: Auto determination of trim5 results: 0 -INFO @ Wed, 14 Feb 2018 01:52:58: Possible gRNA lengths:20 -INFO @ Wed, 14 Feb 2018 01:52:58: Processing 0M reads .. -INFO @ Wed, 14 Feb 2018 01:52:58: Total: 2500. -INFO @ Wed, 14 Feb 2018 01:52:58: Mapped: 1453. -DEBUG @ Wed, 14 Feb 2018 01:52:58: Initial (total) size factor: 1.0 -DEBUG @ Wed, 14 Feb 2018 01:52:58: Median factor: 2.0 -INFO @ Wed, 14 Feb 2018 01:52:58: Final size factor: 2.0 -INFO @ Wed, 14 Feb 2018 01:52:58: Summary of file input.gz: -INFO @ Wed, 14 Feb 2018 01:52:58: label sample1 -INFO @ Wed, 14 Feb 2018 01:52:58: reads 2500 -INFO @ Wed, 14 Feb 2018 01:52:58: mappedreads 1453 -INFO @ Wed, 14 Feb 2018 01:52:58: totalsgrnas 2550 -INFO @ Wed, 14 Feb 2018 01:52:58: zerosgrnas 1276 -INFO @ Wed, 14 Feb 2018 01:52:58: giniindex 0.5266899931488773 -INFO @ Wed, 14 Feb 2018 01:52:58: Loading Rnw template file: /home/maria/miniconda3/envs/mulled-v1-0142cfe25b04f0c1d6899e250fb2f311b2d84778259938a0f6bd1d2ee743fa71/lib/python3.6/site-packages/mageck/fastq_template.Rnw. -DEBUG @ Wed, 14 Feb 2018 01:52:58: Setting up the visualization module... -INFO @ Wed, 14 Feb 2018 01:52:58: Running command: cd ./; Rscript output_countsummary.R -INFO @ Wed, 14 Feb 2018 01:52:58: Command message: -INFO @ Wed, 14 Feb 2018 01:52:58: Writing to file output_countsummary.tex -INFO @ Wed, 14 Feb 2018 01:52:58: Processing code chunks with options ... -INFO @ Wed, 14 Feb 2018 01:52:58: 1 : keep.source term verbatim (label = funcdef, output_countsummary.Rnw:28) -INFO @ Wed, 14 Feb 2018 01:52:58: 2 : keep.source term tex (label = tab1, output_countsummary.Rnw:156) -INFO @ Wed, 14 Feb 2018 01:52:58: 3 : keep.source term tex (label = tab2, output_countsummary.Rnw:174) -INFO @ Wed, 14 Feb 2018 01:52:58: 4 : keep.source term tex (label = tab3, output_countsummary.Rnw:188) -INFO @ Wed, 14 Feb 2018 01:52:58: 5 : keep.source term verbatim pdf (output_countsummary.Rnw:221) -INFO @ Wed, 14 Feb 2018 01:52:58: 6 : keep.source term verbatim pdf (output_countsummary.Rnw:228) -INFO @ Wed, 14 Feb 2018 01:52:58: -INFO @ Wed, 14 Feb 2018 01:52:58: You can now run (pdf)latex on ‘output_countsummary.tex’ -INFO @ Wed, 14 Feb 2018 01:52:58: Error in texi2dvi("output_countsummary.tex", pdf = TRUE) : -INFO @ Wed, 14 Feb 2018 01:52:58: pdflatex is not available -INFO @ Wed, 14 Feb 2018 01:52:58: Execution halted -INFO @ Wed, 14 Feb 2018 01:52:58: -INFO @ Wed, 14 Feb 2018 01:52:58: End command message. +INFO @ Sun, 25 Mar 2018 15:51:06: Parameters: /Users/doylemaria/miniconda3/envs/mulled-v1-5ed9647f14e9d3e99564d31bed2eb19cd32ee8b9da66a89bea59b64a8983b1d6/bin/mageck count -l /private/var/folders/zn/m_qvr9zd7tq0wdtsbq255f8xypj_zg/T/tmp0EKzNL/files/000/dataset_2.dat --fastq input_0.gz --sample-label test1_fastq_gz -n output --pdf-report --keep-tmp --unmapped-to-file +INFO @ Sun, 25 Mar 2018 15:51:06: Welcome to MAGeCK v0.5.7. Command: count +INFO @ Sun, 25 Mar 2018 15:51:06: Loading 2550 predefined sgRNAs. +WARNING @ Sun, 25 Mar 2018 15:51:06: There are 0 sgRNAs with duplicated sequences. +INFO @ Sun, 25 Mar 2018 15:51:06: Parsing FASTQ file input_0.gz... +INFO @ Sun, 25 Mar 2018 15:51:06: Determining the trim-5 length of FASTQ file input_0.gz... +INFO @ Sun, 25 Mar 2018 15:51:06: Possible gRNA lengths:20 +INFO @ Sun, 25 Mar 2018 15:51:06: Processing 0M reads ... +INFO @ Sun, 25 Mar 2018 15:51:06: Read length:30 +INFO @ Sun, 25 Mar 2018 15:51:06: Total tested reads: 2500, mapped: 1453(0.5812) +INFO @ Sun, 25 Mar 2018 15:51:06: --trim-5 test data: (trim_length reads fraction) +INFO @ Sun, 25 Mar 2018 15:51:06: 0 1453 1.0 +INFO @ Sun, 25 Mar 2018 15:51:06: Auto determination of trim5 results: 0 +INFO @ Sun, 25 Mar 2018 15:51:06: Possible gRNA lengths:20 +INFO @ Sun, 25 Mar 2018 15:51:06: Processing 0M reads .. +INFO @ Sun, 25 Mar 2018 15:51:06: Total: 2500. +INFO @ Sun, 25 Mar 2018 15:51:06: Mapped: 1453. +DEBUG @ Sun, 25 Mar 2018 15:51:06: Initial (total) size factor: 1.0 +DEBUG @ Sun, 25 Mar 2018 15:51:06: Median factor: 2.0 +INFO @ Sun, 25 Mar 2018 15:51:06: Final size factor: 2.0 +INFO @ Sun, 25 Mar 2018 15:51:06: Summary of file input_0.gz: +INFO @ Sun, 25 Mar 2018 15:51:06: label test1_fastq_gz +INFO @ Sun, 25 Mar 2018 15:51:06: reads 2500 +INFO @ Sun, 25 Mar 2018 15:51:06: mappedreads 1453 +INFO @ Sun, 25 Mar 2018 15:51:06: totalsgrnas 2550 +INFO @ Sun, 25 Mar 2018 15:51:06: zerosgrnas 1276 +INFO @ Sun, 25 Mar 2018 15:51:06: giniindex 0.5266899931488773 +INFO @ Sun, 25 Mar 2018 15:51:06: Loading Rnw template file: /Users/doylemaria/miniconda3/envs/mulled-v1-5ed9647f14e9d3e99564d31bed2eb19cd32ee8b9da66a89bea59b64a8983b1d6/lib/python3.6/site-packages/mageck/fastq_template.Rnw. +DEBUG @ Sun, 25 Mar 2018 15:51:06: Setting up the visualization module... +INFO @ Sun, 25 Mar 2018 15:51:06: Running command: cd ./; Rscript output_countsummary.R +INFO @ Sun, 25 Mar 2018 15:51:11: Command message: +INFO @ Sun, 25 Mar 2018 15:51:11: Writing to file output_countsummary.tex +INFO @ Sun, 25 Mar 2018 15:51:11: Processing code chunks with options ... +INFO @ Sun, 25 Mar 2018 15:51:11: 1 : keep.source term verbatim (label = funcdef, output_countsummary.Rnw:28) +INFO @ Sun, 25 Mar 2018 15:51:11: 2 : keep.source term tex (label = tab1, output_countsummary.Rnw:156) +INFO @ Sun, 25 Mar 2018 15:51:11: 3 : keep.source term tex (label = tab2, output_countsummary.Rnw:174) +INFO @ Sun, 25 Mar 2018 15:51:11: 4 : keep.source term tex (label = tab3, output_countsummary.Rnw:188) +INFO @ Sun, 25 Mar 2018 15:51:11: 5 : keep.source term verbatim pdf (output_countsummary.Rnw:221) +INFO @ Sun, 25 Mar 2018 15:51:11: 6 : keep.source term verbatim pdf (output_countsummary.Rnw:228) +INFO @ Sun, 25 Mar 2018 15:51:11: +INFO @ Sun, 25 Mar 2018 15:51:11: You can now run (pdf)latex on ‘output_countsummary.tex’ +INFO @ Sun, 25 Mar 2018 15:51:11: +INFO @ Sun, 25 Mar 2018 15:51:11: End command message. |
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| diff -r 80cf607159ae -r 82a180e6b582 test-data/out.count.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/out.count.txt Wed Apr 04 11:03:05 2018 -0400 |
| b |
| b'@@ -0,0 +1,2551 @@\n+sgRNA\tGene\ttest1_fastq_gz\n+s_47512\tRNF111\t1\n+s_24835\tHCFC1R1\t1\n+s_14784\tCYP4B1\t4\n+s_51146\tSLC18A1\t1\n+s_58960\tTRIM5\t1\n+s_48256\tRPRD2\t1\n+s_30297\tKRTAP5-5\t1\n+s_14555\tCYB5B\t1\n+s_39959\tPAAF1\t1\n+s_45293\tPUF60\t1\n+s_49358\tSCN8A\t1\n+s_64995\tZYG11A\t1\n+s_4029\tASTE1\t1\n+s_45554\tR3HDML\t1\n+s_34264\tMMRN1\t1\n+s_37459\tNOL6\t1\n+s_23990\tGPX7\t1\n+s_20268\tFANCC\t1\n+s_14157\tCTLA4\t1\n+s_36773\tNEURL4\t18\n+s_18804\tETFB\t1\n+s_782\tACSS1\t1\n+s_18272\tENPP2\t1\n+s_46620\tRCN1\t1\n+s_55436\tTAS2R3\t1\n+s_57947\tTMPRSS2\t1\n+s_6438\tC14orf159\t1\n+s_33846\tMGST2\t1\n+s_16328\tDNAH6\t1\n+s_17875\tEIF4G1\t1\n+s_2305\tANAPC11\t1\n+s_2500\tANKRD2\t1\n+s_82\tAARSD1\t1\n+s_55329\tTAL1\t1\n+s_57926\tTMPRSS11E\t8\n+s_38414\tNUP98\t4\n+s_50044\tSERPINF1\t1\n+s_9257\tCASR\t1\n+s_63396\tZNF182\t1\n+s_56478\tTHBS3\t1\n+s_17191\tDYRK1A\t1\n+s_11988\tCIR1\t1\n+s_43313\tPPARD\t1\n+s_44681\tPSMA4\t1\n+s_10387\tCD320\t1\n+s_64869\tZPBP\t1\n+s_54385\tSTK17B\t1\n+s_25423\tHIST1H4D\t1\n+s_54172\tST8SIA4\t9\n+s_1161\tADCY10\t1\n+s_29184\tKIAA0913\t1\n+s_42977\tPOLD3\t1\n+s_49449\tSCUBE1\t1\n+s_24181\tGRM4\t1\n+s_52507\tSMARCA5\t1\n+s_28674\tKCNJ10\t1\n+s_61074\tVAMP2\t4\n+s_3954\tASIC2\t1\n+s_2385\tANK1\t1\n+s_18397\tEPDR1\t1\n+s_18377\tEPB41L4B\t1\n+s_34580\tMRAP2\t1\n+s_48676\tRUFY3\t10\n+s_691\tACP1\t1\n+s_30460\tLAMP2\t1\n+s_42637\tPLRG1\t1\n+s_12695\tCNOT6\t1\n+s_33316\tMECOM\t2\n+s_35081\tMSRB2\t1\n+s_58512\tTPD52L2\t1\n+s_19912\tFAM22F\t1\n+s_45517\tQSOX2\t1\n+s_56705\tTINAG\t1\n+s_10946\tCDKL5\t1\n+s_57473\tTMEM211\t2\n+s_57657\tTMEM44\t1\n+s_43200\tPOT1\t1\n+s_19436\tFAM135A\t1\n+s_184\tABCB9\t1\n+s_30171\tKRT84\t1\n+s_44758\tPSMC3IP\t1\n+s_48313\tRPS3\t1\n+s_58142\tTNFSF12\t6\n+s_59718\tTTLL6\t7\n+s_9725\tCCDC43\t1\n+s_5135\tBCKDHA\t1\n+s_36539\tNDUFC2\t1\n+s_27251\tIL27RA\t1\n+s_48939\tSAMD10\t1\n+s_27343\tIL5RA\t1\n+s_28386\tKANK2\t1\n+s_27610\tINSRR\t1\n+s_2769\tAOC3\t2\n+s_58632\tTRA2B\t12\n+s_6674\tC16orf86\t1\n+s_22902\tGJD4\t1\n+s_48278\tRPS15A\t1\n+s_61998\tWIPF2\t1\n+s_4937\tBAIAP3\t2\n+s_54471\tSTOML1\t2\n+s_19157\tFABP12\t1\n+s_5434\tBIN1\t2\n+s_42042\tPIP5K1A\t1\n+s_7794\tC3orf18\t1\n+s_54846\tSVIL\t1\n+s_62273\tXPA\t1\n+s_45859\tRACGAP1\t1\n+s_53626\tSPOCK3\t1\n+s_43295\tPPAP2C\t7\n+s_11788\tCHRDL1\t2\n+s_50636\tSHQ1\t1\n+s_16705\tDPF1\t1\n+s_39741\tOTOF\t1\n+s_27505\tINHBE\t1\n+s_707\tACPL2\t1\n+s_15418\tDDX3Y\t6\n+s_56018\tTEAD4\t1\n+s_44367\tPRR12\t1\n+s_25875\tHOXB5\t1\n+s_49360\tSCN9A\t1\n+s_16244\tDMPK\t1\n+s_3909\tASCC2\t1\n+s_55088\tSYT6\t1\n+s_54311\tSTAU1\t1\n+s_53890\tSRP72\t1\n+s_11035\tCDX1\t1\n+s_18178\tEMR3\t2\n+s_16084\tDLD\t1\n+s_47207\tRHOBTB1\t1\n+s_40267\tPARK2\t6\n+s_43104\tPOLR3B\t1\n+s_2200\tAMDHD2\t1\n+s_12738\tCNRIP1\t1\n+s_17842\tEIF4A3\t1\n+s_57950\tTMPRSS3\t1\n+s_62146\tWRN\t1\n+s_11055\tCEACAM1\t1\n+s_54580\tSTX2\t1\n+s_29277\tKIAA1407\t1\n+s_33428\tMEF2A\t1\n+s_59797\tTUBB\t1\n+s_18113\tEME1\t1\n+s_29839\tKLHL8\t1\n+s_18058\tELP2\t1\n+s_49497\tSDCBP2\t3\n+s_16874\tDRP2\t1\n+s_13572\tCREBL2\t1\n+s_20540\tFBXO30\t1\n+s_64380\tZNF646\t1\n+s_50366\tSH2B1\t1\n+s_2548\tANKRD33B\t1\n+s_41183\tPDXP\t1\n+s_16315\tDNAH12\t1\n+s_19996\tFAM49B\t1\n+s_30751\tLDLRAD3\t1\n+s_36960\tNGEF\t1\n+s_39015\tOR2A2\t1\n+s_26302\tHSPB2\t1\n+s_64297\tZNF611\t5\n+s_730\tACSBG1\t1\n+s_50271\tSFXN4\t1\n+s_8592\tCA6\t2\n+s_13683\tCRMP1\t1\n+s_51103\tSLC16A7\t1\n+s_63785\tZNF384\t1\n+s_16339\tDNAH9\t1\n+s_55936\tTCTEX1D1\t1\n+s_14497\tCXorf40A\t1\n+s_1123\tADAT1\t1\n+s_41304\tPERP\t1\n+s_18719\tESAM\t1\n+s_35118\tMSX2\t1\n+s_30128\tKRT6A\t1\n+s_402\tABTB1\t1\n+s_32578\tMAP1LC3A\t1\n+s_45063\tPTMA\t1\n+s_43551\tPPP1R14D\t1\n+s_2538\tANKRD32\t1\n+s_40384\tPAX1\t1\n+s_29076\tKIAA0101\t1\n+s_40482\tPCDH10\t1\n+s_2348\tANGPT2\t1\n+s_59756\tTTYH3\t1\n+s_34330\tMOB4\t1\n+s_49331\tSCN2B\t1\n+s_54905\tSYDE1\t1\n+s_39101\tOR2T1\t1\n+s_36623\tNEDD4L\t1\n+s_40500\tPCDH15\t2\n+s_10660\tCDC42SE2\t1\n+s_30867\tLGALS13\t1\n+s_24322\tGSTK1\t2\n+s_59167\tTRPC1\t1\n+s_57440\tTMEM201\t1\n+s_50539\tSHC1\t1\n+s_37087\tNIT1\t1\n+s_56345\tTGFB2\t1\n+s_55388\tTARM1\t1\n+s_1224\tADD2\t1\n+s_5256\tBCOR\t2\n+s_51731\tSLC35B3\t1\n+s_12987\tCOL6A6\t1\n+s_56745\tTJP3\t1\n+s_19340\tFAM120AOS\t1\n+s_53904\tSRPR\t1\n+s_1588\tAGXT\t1\n+s_46157\tRASA3\t1\n+s_19166\tFABP3\t7\n+s_22330\tGATM\t1\n+s_10731\tCDH13\t1\n+s_2329\tANAPC5\t1\n+s_46045\tRANGAP1\t1\n+s_54814\tSUV39H2\t1\n+s_56169\tTEX14\t1\n+s_3433\tARHGEF26\t1\n+s_48032\tRP4-811H24.6\t1\n+s_51930\tSLC41A3\t1\n+s_63893\tZNF433\t1\n+s_46996\tRGCC\t1\n+s_13863\tCSF3R\t1\n+s_26337\tHSPH1\t1\n+s_12983\tCOL6A3\t1\n+s_1376\tADSS\t1\n+s_45449\tPYHIN1\t1\n+s_49629\tSEC22C\t1\n+s_20204\tFAM86A\t1\n+s_24920\tHDAC9\t1\n+s_14961\tDAPK1\t1\n+s_'..b'A\t0\n+s_57422\tTMEM198\t0\n+s_57429\tTMEM2\t0\n+s_57475\tTMEM212\t0\n+s_57531\tTMEM231\t0\n+s_57568\tTMEM245\t0\n+s_57700\tTMEM54\t0\n+s_57873\tTMF1\t0\n+s_57992\tTMUB1\t0\n+s_58180\tTNIP1\t0\n+s_58211\tTNKS2\t0\n+s_58237\tTNNT1\t0\n+s_58256\tTNPO2\t0\n+s_58259\tTNPO3\t0\n+s_58309\tTOM1\t0\n+s_58485\tTP73\t0\n+s_58503\tTPD52\t0\n+s_58533\tTPI1\t0\n+s_5857\tBSPRY\t0\n+s_58612\tTPSG1\t0\n+s_58633\tTRA2B\t0\n+s_58655\tTRAF3\t0\n+s_58668\tTRAF3IP2\t0\n+s_58690\tTRAK1\t0\n+s_58809\tTRIB2\t0\n+s_58962\tTRIM50\t0\n+s_58968\tTRIM52\t0\n+s_59050\tTRIO\t0\n+s_59107\tTRMT1L\t0\n+s_59133\tTRMT61B\t0\n+s_59160\tTROVE2\t0\n+s_59173\tTRPC4\t0\n+s_59196\tTRPM1\t0\n+s_59204\tTRPM3\t0\n+s_59311\tTSEN54\t0\n+s_59332\tTSHB\t0\n+s_59340\tTSHZ2\t0\n+s_59360\tTSNARE1\t0\n+s_5952\tBTG4\t0\n+s_59539\tTTC21A\t0\n+s_59602\tTTC39A\t0\n+s_59654\tTTC9C\t0\n+s_59717\tTTLL6\t0\n+s_5974\tBTN3A1\t0\n+s_59748\tTTYH1\t0\n+s_59807\tTUBB2B\t0\n+s_59859\tTULP1\t0\n+s_59870\tTULP3\t0\n+s_59955\tTXNDC8\t0\n+s_59983\tTXNRD2\t0\n+s_600\tACE\t0\n+s_60169\tUBE2H\t0\n+s_60209\tUBE2Q2\t0\n+s_60237\tUBE2V2\t0\n+s_60248\tUBE3A\t0\n+s_60250\tUBE3B\t0\n+s_60373\tUBXN6\t0\n+s_60396\tUCKL1\t0\n+s_60423\tUEVLD\t0\n+s_60438\tUFSP1\t0\n+s_60449\tUGDH\t0\n+s_60517\tUGT2A1\t0\n+s_60542\tUGT3A1\t0\n+s_60603\tUMODL1\t0\n+s_60614\tUNC119\t0\n+s_60649\tUNC5B\t0\n+s_6068\tC10orf125\t0\n+s_6071\tC10orf128\t0\n+s_60753\tUQCRC2\t0\n+s_60780\tURM1\t0\n+s_60839\tUSP15\t0\n+s_60851\tUSP19\t0\n+s_60925\tUSP4\t0\n+s_6100\tC10orf53\t0\n+s_6106\tC10orf54\t0\n+s_61149\tVAV2\t0\n+s_61173\tVCAM1\t0\n+s_61178\tVCAN\t0\n+s_61221\tVEPH1\t0\n+s_61263\tVIL1\t0\n+s_61341\tVPS13C\t0\n+s_61344\tVPS13D\t0\n+s_61367\tVPS29\t0\n+s_61529\tVWA5A\t0\n+s_61531\tVWA5A\t0\n+s_61587\tWBP1\t0\n+s_61595\tWBP2\t0\n+s_61623\tWDFY1\t0\n+s_61640\tWDHD1\t0\n+s_61662\tWDR16\t0\n+s_61695\tWDR26\t0\n+s_61739\tWDR44\t0\n+s_6200\tC11orf49\t0\n+s_62019\tWISP1\t0\n+s_62098\tWNT5B\t0\n+s_62114\tWNT8A\t0\n+s_62171\tWTAP\t0\n+s_62249\tXKR3\t0\n+s_62257\tXKR6\t0\n+s_62275\tXPC\t0\n+s_62320\tXRCC4\t0\n+s_62361\tYAE1D1\t0\n+s_62550\tZBBX\t0\n+s_62559\tZBED6\t0\n+s_62567\tZBTB1\t0\n+s_62624\tZBTB37\t0\n+s_62657\tZBTB47\t0\n+s_62759\tZC3H7A\t0\n+s_62845\tZDHHC11\t0\n+s_62862\tZDHHC16\t0\n+s_62881\tZDHHC2\t0\n+s_6292\tC12orf23\t0\n+s_62975\tZFC3H1\t0\n+s_63034\tZFP64\t0\n+s_63104\tZFYVE27\t0\n+s_63107\tZFYVE27\t0\n+s_63114\tZFYVE28\t0\n+s_63217\tZMIZ2\t0\n+s_63228\tZMYM3\t0\n+s_63234\tZMYM3\t0\n+s_6326\tC12orf49\t0\n+s_63302\tZNF132\t0\n+s_63362\tZNF167\t0\n+s_63435\tZNF200\t0\n+s_63487\tZNF223\t0\n+s_63594\tZNF276\t0\n+s_636\tACO1\t0\n+s_63746\tZNF354B\t0\n+s_63755\tZNF362\t0\n+s_6376\tC12orf74\t0\n+s_63903\tZNF436\t0\n+s_63905\tZNF438\t0\n+s_63923\tZNF442\t0\n+s_63934\tZNF445\t0\n+s_63935\tZNF446\t0\n+s_63964\tZNF469\t0\n+s_63983\tZNF480\t0\n+s_6409\tC14orf105\t0\n+s_64137\tZNF554\t0\n+s_64241\tZNF586\t0\n+s_6427\tC14orf133\t0\n+s_64356\tZNF639\t0\n+s_64393\tZNF655\t0\n+s_64396\tZNF655\t0\n+s_64419\tZNF668\t0\n+s_64424\tZNF669\t0\n+s_64459\tZNF682\t0\n+s_64479\tZNF688\t0\n+s_64581\tZNF746\t0\n+s_64627\tZNF772\t0\n+s_64638\tZNF776\t0\n+s_64652\tZNF780A\t0\n+s_64791\tZNF85\t0\n+s_64851\tZNRF3\t0\n+s_64871\tZPBP\t0\n+s_64878\tZPLD1\t0\n+s_64898\tZSCAN10\t0\n+s_64930\tZSCAN30\t0\n+s_64997\tZYG11A\t0\n+s_6525\tC15orf39\t0\n+s_6592\tC16orf13\t0\n+s_6639\tC16orf62\t0\n+s_6707\tC17orf102\t0\n+s_6710\tC17orf104\t0\n+s_6728\tC17orf112\t0\n+s_6736\tC17orf39\t0\n+s_6794\tC17orf72\t0\n+s_6814\tC17orf80\t0\n+s_6849\tC18orf21\t0\n+s_6859\tC18orf32\t0\n+s_6862\tC18orf34\t0\n+s_6906\tC19orf38\t0\n+s_7053\tC1QTNF7\t0\n+s_7128\tC1orf122\t0\n+s_7144\tC1orf130\t0\n+s_7162\tC1orf144\t0\n+s_7234\tC1orf198\t0\n+s_7341\tC1orf63\t0\n+s_747\tACSL1\t0\n+s_76\tAARS2\t0\n+s_7674\tC2orf57\t0\n+s_7681\tC2orf62\t0\n+s_7692\tC2orf63\t0\n+s_77\tAARSD1\t0\n+s_78\tAARSD1\t0\n+s_781\tACSS1\t0\n+s_786\tACSS2\t0\n+s_7940\tC4orf26\t0\n+s_7970\tC4orf37\t0\n+s_8000\tC4orf52\t0\n+s_804\tACTB\t0\n+s_8073\tC5orf51\t0\n+s_8141\tC6orf162\t0\n+s_8227\tC7orf10\t0\n+s_8281\tC7orf59\t0\n+s_8318\tC8A\t0\n+s_8403\tC9orf100\t0\n+s_8470\tC9orf24\t0\n+s_8699\tCACNA1G\t0\n+s_8705\tCACNA1I\t0\n+s_871\tACTR8\t0\n+s_874\tACTR8\t0\n+s_8757\tCACNG5\t0\n+s_8797\tCADPS\t0\n+s_8879\tCALR\t0\n+s_8910\tCAMK2B\t0\n+s_893\tACVR1B\t0\n+s_8930\tCAMKK1\t0\n+s_8954\tCAMSAP1\t0\n+s_9064\tCAPRIN1\t0\n+s_9077\tCAPSL\t0\n+s_9109\tCARD17\t0\n+s_913\tACY1\t0\n+s_9171\tCASD1\t0\n+s_9196\tCASP10\t0\n+s_9285\tCATSPER3\t0\n+s_9506\tCCDC120\t0\n+s_9507\tCCDC121\t0\n+s_952\tADAM12\t0\n+s_9584\tCCDC149\t0\n+s_964\tADAM18\t0\n+s_9646\tCCDC170\t0\n+s_9710\tCCDC40\t0\n+s_9732\tCCDC48\t0\n+s_976\tADAM21\t0\n+s_9763\tCCDC62\t0\n+s_9868\tCCDC89\t0\n+s_991\tADAM30\t0\n+s_9925\tCCL1\t0\n+s_9973\tCCL26\t0\n' |
| b |
| diff -r 80cf607159ae -r 82a180e6b582 test-data/out.count_multi.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/out.count_multi.txt Wed Apr 04 11:03:05 2018 -0400 |
| b |
| b'@@ -0,0 +1,2551 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| diff -r 80cf607159ae -r 82a180e6b582 test-data/out.countsummary.txt --- a/test-data/out.countsummary.txt Sat Feb 17 10:41:13 2018 -0500 +++ b/test-data/out.countsummary.txt Wed Apr 04 11:03:05 2018 -0400 |
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| @@ -1,2 +1,2 @@ File Label Reads Mapped Percentage TotalsgRNAs Zerocounts GiniIndex NegSelQC NegSelQCPval NegSelQCPvalPermutation NegSelQCPvalPermutationFDR NegSelQCGene -input.gz sample1 2500 1453 0.5812 2550 1276 0.5267 0 1 1 1 0.0 +input_0.gz test1_fastq_gz 2500 1453 0.5812 2550 1276 0.5267 0 1 1 1 0.0 |
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| diff -r 80cf607159ae -r 82a180e6b582 test-data/out.countsummary_multi.pdf |
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| Binary file test-data/out.countsummary_multi.pdf has changed |
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| diff -r 80cf607159ae -r 82a180e6b582 test-data/out.mle.log.txt --- a/test-data/out.mle.log.txt Sat Feb 17 10:41:13 2018 -0500 +++ b/test-data/out.mle.log.txt Wed Apr 04 11:03:05 2018 -0400 |
| [ |
| b'@@ -1,749 +1,57 @@\n-INFO @ Mon, 12 Feb 2018 21:46:26: Parameters: /home/maria/miniconda3/envs/mulled-v1-b1e6893952d2d7e4d51a13d040adcd7bea052bfdc57a24d59056014db875e749/bin/mageck mle -k /tmp/tmpRFR3vr/files/000/dataset_1.dat -d /tmp/tmpRFR3vr/files/000/dataset_2.dat -n output --norm-method median --genes-varmodeling 1000 --permutation-round 10 --adjust-method fdr --threads 1 \n-INFO @ Mon, 12 Feb 2018 21:46:27: Cannot parse design matrix as a string; try to parse it as a file name ... \n-INFO @ Mon, 12 Feb 2018 21:46:27: Design matrix: \n-INFO @ Mon, 12 Feb 2018 21:46:27: [[1. 0. 0.] \n-INFO @ Mon, 12 Feb 2018 21:46:27: [1. 0. 0.] \n-INFO @ Mon, 12 Feb 2018 21:46:27: [1. 1. 0.] \n-INFO @ Mon, 12 Feb 2018 21:46:27: [1. 0. 1.]] \n-INFO @ Mon, 12 Feb 2018 21:46:27: Beta labels:baseline,HL60,KBM7 \n-INFO @ Mon, 12 Feb 2018 21:46:27: Included samples:HL60.initial,KBM7.initial,HL60.final,KBM7.final \n-INFO @ Mon, 12 Feb 2018 21:46:27: Loaded samples:HL60.initial;KBM7.initial;HL60.final;KBM7.final \n-INFO @ Mon, 12 Feb 2018 21:46:27: Sample index: 0;1;2;3 \n-INFO @ Mon, 12 Feb 2018 21:46:27: Loaded 100 genes. \n-DEBUG @ Mon, 12 Feb 2018 21:46:27: Initial (total) size factor: 1.6654412961322171 2.025116092944715 0.720025234995028 0.6592307725342162 \n-DEBUG @ Mon, 12 Feb 2018 21:46:27: Median factor: 1.4705915949061357 1.773663484525946 0.6311218804203026 0.5731039100868989 \n-INFO @ Mon, 12 Feb 2018 21:46:27: Final size factor: 1.4705915949061357 1.773663484525946 0.6311218804203026 0.5731039100868989 \n-INFO @ Mon, 12 Feb 2018 21:46:27: size factor: 0.6799984465189518,0.5638048078028025,1.5844800046134337,1.744884273862957 \n-INFO @ Mon, 12 Feb 2018 21:46:27: Thread 0 started. \n-INFO @ Mon, 12 Feb 2018 21:46:27: Thread 0: total 100 instances. \n-INFO @ Mon, 12 Feb 2018 21:46:27: Thread 0: Calculating AAAS (1) ... \n-INFO @ Mon, 12 Feb 2018 21:46:27: Thread 0 completed. \n-INFO @ Mon, 12 Feb 2018 21:46:27: All threads completed. \n-INFO @ Mon, 12 Feb 2018 21:46:27: Modeling the mean and variance ... \n-INFO @ Mon, 12 Feb 2018 21:46:27: Linear regression: y=-0.902175602829449x+14.539230037913281 \n-INFO @ Mon, 12 Feb 2018 21:46:27: Run the algorithm for the second time ... \n-WARNING @ Mon, 12 Feb 2018 21:46:27: A1CF: beta value does not converge. Try to increase the value of alpha .. \n-WARNING @ Mon, 12 Feb 2018 21:46:27: A1CF: alpha: 0.01 \n-WARNING @ Mon, 12 Feb 2018 21:46:28: A1CF: reaches the maximum number of iterations. \n-WARNING @ Mon, 12 Feb 2018 21:46:28: A1CF: alpha: 0.03 \n-WARNING @ Mon, 12 Feb 2018 21:46:29: A1CF: reaches the maximum number of iterations. \n-WARNING @ Mon, 12 Feb 2018 21:46:29: A1CF: alpha: 0.09 \n-INFO @ Mon, 12 Feb 2018 21:46:29: Calculating AAAS (1) ... \n-WARNING @ Mon, 12 Feb 2018 21:46:29: AAAS: beta value does not converge. Try to increase the value of alpha .. \n-WARNING @ Mon, 12 Feb 2018 21:46:29: AAAS: alpha: 0.01 \n-WARNING @ Mon, 12 Feb 2018 21:46:30: AAAS: reaches the maximum number of iterations. \n-WARNING @ Mon, 12 Feb 2018 21:46:30: AAAS: alpha: 0.03 \n-WARNING @ Mon, 12 Feb 2018 21:46:31: AAAS: reaches the maximum number of iterations. \n-WARNING @ Mon, 12 Feb 2018 21:46:31: AAAS: alpha: 0.09 \n-WARNING @ Mon, 12 Feb 2018 21:46:31: AAK1: beta value does not converge. Try to increase the value of alpha .. \n-WARNING @ Mon, 12 Feb 2018 21:46:31: AAK1: alpha: 0.01 \n-WARNING @ Mon, 12 Feb 2018 21:46:31: AAK1: reaches the maximum number of iterations. \n-WARNING @ Mon, 12 Feb 2018 21:46:31: AAK1: alpha: 0.03 \n-WARNING @ Mon, 12 Feb 2018 21:46:32: AAK1: reaches the maximum number of iterations. \n-WARNING @ Mon, 12 Feb 2018 21:46:32: AAK1: alpha: 0.09 \n-WARNING @ Mon, 12 Feb 2018 21:46:32: AATF: beta value does not converge. Try to increase the value of alpha .. \n-WARNING @ Mon, 12 Feb 2018 21:46:32: AATF: alpha: 0.01 \n-WARNING @ Mon, 12 Feb 2018 21:46:33: AATF: reaches the maximum number of iterations. \n-WARNING @ Mon, 12 Feb 2018 21:46:33: AATF: alpha: 0.03 \n-WARNING @ Mon, 12 Feb 2018 21:46:33: '..b'ds 1 \n+INFO @ Sun, 25 Mar 2018 22:27:42: Cannot parse design matrix as a string; try to parse it as a file name ... \n+INFO @ Sun, 25 Mar 2018 22:27:42: Design matrix: \n+INFO @ Sun, 25 Mar 2018 22:27:42: [[1. 0. 0.] \n+INFO @ Sun, 25 Mar 2018 22:27:42: [1. 0. 0.] \n+INFO @ Sun, 25 Mar 2018 22:27:42: [1. 1. 0.] \n+INFO @ Sun, 25 Mar 2018 22:27:42: [1. 0. 1.]] \n+INFO @ Sun, 25 Mar 2018 22:27:42: Beta labels:baseline,HL60,KBM7 \n+INFO @ Sun, 25 Mar 2018 22:27:42: Included samples:HL60.initial,KBM7.initial,HL60.final,KBM7.final \n+INFO @ Sun, 25 Mar 2018 22:27:42: Loaded samples:HL60.initial;KBM7.initial;HL60.final;KBM7.final \n+INFO @ Sun, 25 Mar 2018 22:27:42: Sample index: 0;1;2;3 \n+INFO @ Sun, 25 Mar 2018 22:27:42: Loaded 100 genes. \n+DEBUG @ Sun, 25 Mar 2018 22:27:42: Initial (total) size factor: 1.6654412961322171 2.025116092944715 0.720025234995028 0.6592307725342162 \n+DEBUG @ Sun, 25 Mar 2018 22:27:42: Median factor: 1.4705915949061357 1.773663484525946 0.6311218804203026 0.5731039100868989 \n+INFO @ Sun, 25 Mar 2018 22:27:42: Final size factor: 1.4705915949061357 1.773663484525946 0.6311218804203026 0.5731039100868989 \n+INFO @ Sun, 25 Mar 2018 22:27:42: size factor: 0.6799984465189518,0.5638048078028025,1.5844800046134337,1.744884273862957 \n+INFO @ Sun, 25 Mar 2018 22:27:42: Thread 0 started. \n+INFO @ Sun, 25 Mar 2018 22:27:42: Thread 0: total 1 instances. \n+INFO @ Sun, 25 Mar 2018 22:27:42: Thread 0 completed. \n+INFO @ Sun, 25 Mar 2018 22:27:42: All threads completed. \n+INFO @ Sun, 25 Mar 2018 22:27:42: Modeling the mean and variance ... \n+INFO @ Sun, 25 Mar 2018 22:27:42: Run the algorithm for the second time ... \n+INFO @ Sun, 25 Mar 2018 22:27:42: Calculating AAAS (1) ... \n+INFO @ Sun, 25 Mar 2018 22:27:43: Permuting groups of gene with 9 sgRNAs per gene. Group progress: 1/2 \n+INFO @ Sun, 25 Mar 2018 22:27:43: Start permuting 2 rounds ... \n+INFO @ Sun, 25 Mar 2018 22:27:43: Collecting 999 sgRNAs from 100 genes. \n+INFO @ Sun, 25 Mar 2018 22:27:43: Permuting round 0 ... \n+INFO @ Sun, 25 Mar 2018 22:27:43: Thread 0 started. \n+INFO @ Sun, 25 Mar 2018 22:27:43: Thread 0: total 100 instances. \n+INFO @ Sun, 25 Mar 2018 22:27:43: Thread 0: Calculating AAAS (1) ... \n+INFO @ Sun, 25 Mar 2018 22:27:45: Thread 0 completed. \n+INFO @ Sun, 25 Mar 2018 22:27:45: All threads completed. \n+INFO @ Sun, 25 Mar 2018 22:27:45: Permuting round 1 ... \n+INFO @ Sun, 25 Mar 2018 22:27:45: Thread 0 started. \n+INFO @ Sun, 25 Mar 2018 22:27:45: Thread 0: total 100 instances. \n+INFO @ Sun, 25 Mar 2018 22:27:45: Thread 0: Calculating AAAS (1) ... \n+INFO @ Sun, 25 Mar 2018 22:27:46: Thread 0 completed. \n+INFO @ Sun, 25 Mar 2018 22:27:46: All threads completed. \n+INFO @ Sun, 25 Mar 2018 22:27:46: Assigning p values... \n+INFO @ Sun, 25 Mar 2018 22:27:46: Permuting groups of gene with 10 sgRNAs per gene. Group progress: 2/2 \n+INFO @ Sun, 25 Mar 2018 22:27:46: Start permuting 2 rounds ... \n+INFO @ Sun, 25 Mar 2018 22:27:46: Collecting 999 sgRNAs from 100 genes. \n+INFO @ Sun, 25 Mar 2018 22:27:46: Permuting round 0 ... \n+INFO @ Sun, 25 Mar 2018 22:27:47: Thread 0 started. \n+INFO @ Sun, 25 Mar 2018 22:27:47: Thread 0: total 100 instances. \n+INFO @ Sun, 25 Mar 2018 22:27:47: Thread 0: Calculating AAAS (1) ... \n+INFO @ Sun, 25 Mar 2018 22:27:48: Thread 0 completed. \n+INFO @ Sun, 25 Mar 2018 22:27:48: All threads completed. \n+INFO @ Sun, 25 Mar 2018 22:27:49: Permuting round 1 ... \n+INFO @ Sun, 25 Mar 2018 22:27:49: Thread 0 started. \n+INFO @ Sun, 25 Mar 2018 22:27:49: Thread 0: total 100 instances. \n+INFO @ Sun, 25 Mar 2018 22:27:49: Thread 0: Calculating AAAS (1) ... \n+INFO @ Sun, 25 Mar 2018 22:27:50: Thread 0 completed. \n+INFO @ Sun, 25 Mar 2018 22:27:50: All threads completed. \n+INFO @ Sun, 25 Mar 2018 22:27:50: Assigning p values... \n+INFO @ Sun, 25 Mar 2018 22:27:50: Writing gene results to output.gene_summary.txt \n+INFO @ Sun, 25 Mar 2018 22:27:50: Writing sgRNA results to output.sgrna_summary.txt \n' |
| b |
| diff -r 80cf607159ae -r 82a180e6b582 test-data/out.normcounts.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/out.normcounts.txt Wed Apr 04 11:03:05 2018 -0400 |
| b |
| b'@@ -0,0 +1,2551 @@\n+sgRNA\tGene\ttest1_fastq_gz\n+s_47512\tRNF111\t2.0\n+s_24835\tHCFC1R1\t2.0\n+s_14784\tCYP4B1\t8.0\n+s_51146\tSLC18A1\t2.0\n+s_58960\tTRIM5\t2.0\n+s_48256\tRPRD2\t2.0\n+s_30297\tKRTAP5-5\t2.0\n+s_14555\tCYB5B\t2.0\n+s_39959\tPAAF1\t2.0\n+s_45293\tPUF60\t2.0\n+s_49358\tSCN8A\t2.0\n+s_64995\tZYG11A\t2.0\n+s_4029\tASTE1\t2.0\n+s_45554\tR3HDML\t2.0\n+s_34264\tMMRN1\t2.0\n+s_37459\tNOL6\t2.0\n+s_23990\tGPX7\t2.0\n+s_20268\tFANCC\t2.0\n+s_14157\tCTLA4\t2.0\n+s_36773\tNEURL4\t36.0\n+s_18804\tETFB\t2.0\n+s_782\tACSS1\t2.0\n+s_18272\tENPP2\t2.0\n+s_46620\tRCN1\t2.0\n+s_55436\tTAS2R3\t2.0\n+s_57947\tTMPRSS2\t2.0\n+s_6438\tC14orf159\t2.0\n+s_33846\tMGST2\t2.0\n+s_16328\tDNAH6\t2.0\n+s_17875\tEIF4G1\t2.0\n+s_2305\tANAPC11\t2.0\n+s_2500\tANKRD2\t2.0\n+s_82\tAARSD1\t2.0\n+s_55329\tTAL1\t2.0\n+s_57926\tTMPRSS11E\t16.0\n+s_38414\tNUP98\t8.0\n+s_50044\tSERPINF1\t2.0\n+s_9257\tCASR\t2.0\n+s_63396\tZNF182\t2.0\n+s_56478\tTHBS3\t2.0\n+s_17191\tDYRK1A\t2.0\n+s_11988\tCIR1\t2.0\n+s_43313\tPPARD\t2.0\n+s_44681\tPSMA4\t2.0\n+s_10387\tCD320\t2.0\n+s_64869\tZPBP\t2.0\n+s_54385\tSTK17B\t2.0\n+s_25423\tHIST1H4D\t2.0\n+s_54172\tST8SIA4\t18.0\n+s_1161\tADCY10\t2.0\n+s_29184\tKIAA0913\t2.0\n+s_42977\tPOLD3\t2.0\n+s_49449\tSCUBE1\t2.0\n+s_24181\tGRM4\t2.0\n+s_52507\tSMARCA5\t2.0\n+s_28674\tKCNJ10\t2.0\n+s_61074\tVAMP2\t8.0\n+s_3954\tASIC2\t2.0\n+s_2385\tANK1\t2.0\n+s_18397\tEPDR1\t2.0\n+s_18377\tEPB41L4B\t2.0\n+s_34580\tMRAP2\t2.0\n+s_48676\tRUFY3\t20.0\n+s_691\tACP1\t2.0\n+s_30460\tLAMP2\t2.0\n+s_42637\tPLRG1\t2.0\n+s_12695\tCNOT6\t2.0\n+s_33316\tMECOM\t4.0\n+s_35081\tMSRB2\t2.0\n+s_58512\tTPD52L2\t2.0\n+s_19912\tFAM22F\t2.0\n+s_45517\tQSOX2\t2.0\n+s_56705\tTINAG\t2.0\n+s_10946\tCDKL5\t2.0\n+s_57473\tTMEM211\t4.0\n+s_57657\tTMEM44\t2.0\n+s_43200\tPOT1\t2.0\n+s_19436\tFAM135A\t2.0\n+s_184\tABCB9\t2.0\n+s_30171\tKRT84\t2.0\n+s_44758\tPSMC3IP\t2.0\n+s_48313\tRPS3\t2.0\n+s_58142\tTNFSF12\t12.0\n+s_59718\tTTLL6\t14.0\n+s_9725\tCCDC43\t2.0\n+s_5135\tBCKDHA\t2.0\n+s_36539\tNDUFC2\t2.0\n+s_27251\tIL27RA\t2.0\n+s_48939\tSAMD10\t2.0\n+s_27343\tIL5RA\t2.0\n+s_28386\tKANK2\t2.0\n+s_27610\tINSRR\t2.0\n+s_2769\tAOC3\t4.0\n+s_58632\tTRA2B\t24.0\n+s_6674\tC16orf86\t2.0\n+s_22902\tGJD4\t2.0\n+s_48278\tRPS15A\t2.0\n+s_61998\tWIPF2\t2.0\n+s_4937\tBAIAP3\t4.0\n+s_54471\tSTOML1\t4.0\n+s_19157\tFABP12\t2.0\n+s_5434\tBIN1\t4.0\n+s_42042\tPIP5K1A\t2.0\n+s_7794\tC3orf18\t2.0\n+s_54846\tSVIL\t2.0\n+s_62273\tXPA\t2.0\n+s_45859\tRACGAP1\t2.0\n+s_53626\tSPOCK3\t2.0\n+s_43295\tPPAP2C\t14.0\n+s_11788\tCHRDL1\t4.0\n+s_50636\tSHQ1\t2.0\n+s_16705\tDPF1\t2.0\n+s_39741\tOTOF\t2.0\n+s_27505\tINHBE\t2.0\n+s_707\tACPL2\t2.0\n+s_15418\tDDX3Y\t12.0\n+s_56018\tTEAD4\t2.0\n+s_44367\tPRR12\t2.0\n+s_25875\tHOXB5\t2.0\n+s_49360\tSCN9A\t2.0\n+s_16244\tDMPK\t2.0\n+s_3909\tASCC2\t2.0\n+s_55088\tSYT6\t2.0\n+s_54311\tSTAU1\t2.0\n+s_53890\tSRP72\t2.0\n+s_11035\tCDX1\t2.0\n+s_18178\tEMR3\t4.0\n+s_16084\tDLD\t2.0\n+s_47207\tRHOBTB1\t2.0\n+s_40267\tPARK2\t12.0\n+s_43104\tPOLR3B\t2.0\n+s_2200\tAMDHD2\t2.0\n+s_12738\tCNRIP1\t2.0\n+s_17842\tEIF4A3\t2.0\n+s_57950\tTMPRSS3\t2.0\n+s_62146\tWRN\t2.0\n+s_11055\tCEACAM1\t2.0\n+s_54580\tSTX2\t2.0\n+s_29277\tKIAA1407\t2.0\n+s_33428\tMEF2A\t2.0\n+s_59797\tTUBB\t2.0\n+s_18113\tEME1\t2.0\n+s_29839\tKLHL8\t2.0\n+s_18058\tELP2\t2.0\n+s_49497\tSDCBP2\t6.0\n+s_16874\tDRP2\t2.0\n+s_13572\tCREBL2\t2.0\n+s_20540\tFBXO30\t2.0\n+s_64380\tZNF646\t2.0\n+s_50366\tSH2B1\t2.0\n+s_2548\tANKRD33B\t2.0\n+s_41183\tPDXP\t2.0\n+s_16315\tDNAH12\t2.0\n+s_19996\tFAM49B\t2.0\n+s_30751\tLDLRAD3\t2.0\n+s_36960\tNGEF\t2.0\n+s_39015\tOR2A2\t2.0\n+s_26302\tHSPB2\t2.0\n+s_64297\tZNF611\t10.0\n+s_730\tACSBG1\t2.0\n+s_50271\tSFXN4\t2.0\n+s_8592\tCA6\t4.0\n+s_13683\tCRMP1\t2.0\n+s_51103\tSLC16A7\t2.0\n+s_63785\tZNF384\t2.0\n+s_16339\tDNAH9\t2.0\n+s_55936\tTCTEX1D1\t2.0\n+s_14497\tCXorf40A\t2.0\n+s_1123\tADAT1\t2.0\n+s_41304\tPERP\t2.0\n+s_18719\tESAM\t2.0\n+s_35118\tMSX2\t2.0\n+s_30128\tKRT6A\t2.0\n+s_402\tABTB1\t2.0\n+s_32578\tMAP1LC3A\t2.0\n+s_45063\tPTMA\t2.0\n+s_43551\tPPP1R14D\t2.0\n+s_2538\tANKRD32\t2.0\n+s_40384\tPAX1\t2.0\n+s_29076\tKIAA0101\t2.0\n+s_40482\tPCDH10\t2.0\n+s_2348\tANGPT2\t2.0\n+s_59756\tTTYH3\t2.0\n+s_34330\tMOB4\t2.0\n+s_49331\tSCN2B\t2.0\n+s_54905\tSYDE1\t2.0\n+s_39101\tOR2T1\t2.0\n+s_36623\tNEDD4L\t2.0\n+s_40500\tPCDH15\t4.0\n+s_10660\tCDC42SE2\t2.0\n+s_30867\tLGALS13\t2.0\n+s_24322\tGSTK1\t4.0\n+s_59167\tTRPC1\t2.0\n+s_57440\tTMEM201\t2.0\n+s_50539\tSHC1\t2.0\n+s_37087\tNIT1\t2.0\n+s_56345\tTGFB2\t2.0\n+s_55388\tTARM1\t2.0\n+s_1224\tADD2\t2.0\n+s_5256\tBCOR\t4.0\n+s_51731\tSLC35B3\t2.0\n+s_12987\tCOL6A6\t2.0\n+s_56745\tTJP3\t2.0\n+s_19340\tFAM120AOS\t2.0\n+s_53904'..b'A\t0\n+s_57422\tTMEM198\t0\n+s_57429\tTMEM2\t0\n+s_57475\tTMEM212\t0\n+s_57531\tTMEM231\t0\n+s_57568\tTMEM245\t0\n+s_57700\tTMEM54\t0\n+s_57873\tTMF1\t0\n+s_57992\tTMUB1\t0\n+s_58180\tTNIP1\t0\n+s_58211\tTNKS2\t0\n+s_58237\tTNNT1\t0\n+s_58256\tTNPO2\t0\n+s_58259\tTNPO3\t0\n+s_58309\tTOM1\t0\n+s_58485\tTP73\t0\n+s_58503\tTPD52\t0\n+s_58533\tTPI1\t0\n+s_5857\tBSPRY\t0\n+s_58612\tTPSG1\t0\n+s_58633\tTRA2B\t0\n+s_58655\tTRAF3\t0\n+s_58668\tTRAF3IP2\t0\n+s_58690\tTRAK1\t0\n+s_58809\tTRIB2\t0\n+s_58962\tTRIM50\t0\n+s_58968\tTRIM52\t0\n+s_59050\tTRIO\t0\n+s_59107\tTRMT1L\t0\n+s_59133\tTRMT61B\t0\n+s_59160\tTROVE2\t0\n+s_59173\tTRPC4\t0\n+s_59196\tTRPM1\t0\n+s_59204\tTRPM3\t0\n+s_59311\tTSEN54\t0\n+s_59332\tTSHB\t0\n+s_59340\tTSHZ2\t0\n+s_59360\tTSNARE1\t0\n+s_5952\tBTG4\t0\n+s_59539\tTTC21A\t0\n+s_59602\tTTC39A\t0\n+s_59654\tTTC9C\t0\n+s_59717\tTTLL6\t0\n+s_5974\tBTN3A1\t0\n+s_59748\tTTYH1\t0\n+s_59807\tTUBB2B\t0\n+s_59859\tTULP1\t0\n+s_59870\tTULP3\t0\n+s_59955\tTXNDC8\t0\n+s_59983\tTXNRD2\t0\n+s_600\tACE\t0\n+s_60169\tUBE2H\t0\n+s_60209\tUBE2Q2\t0\n+s_60237\tUBE2V2\t0\n+s_60248\tUBE3A\t0\n+s_60250\tUBE3B\t0\n+s_60373\tUBXN6\t0\n+s_60396\tUCKL1\t0\n+s_60423\tUEVLD\t0\n+s_60438\tUFSP1\t0\n+s_60449\tUGDH\t0\n+s_60517\tUGT2A1\t0\n+s_60542\tUGT3A1\t0\n+s_60603\tUMODL1\t0\n+s_60614\tUNC119\t0\n+s_60649\tUNC5B\t0\n+s_6068\tC10orf125\t0\n+s_6071\tC10orf128\t0\n+s_60753\tUQCRC2\t0\n+s_60780\tURM1\t0\n+s_60839\tUSP15\t0\n+s_60851\tUSP19\t0\n+s_60925\tUSP4\t0\n+s_6100\tC10orf53\t0\n+s_6106\tC10orf54\t0\n+s_61149\tVAV2\t0\n+s_61173\tVCAM1\t0\n+s_61178\tVCAN\t0\n+s_61221\tVEPH1\t0\n+s_61263\tVIL1\t0\n+s_61341\tVPS13C\t0\n+s_61344\tVPS13D\t0\n+s_61367\tVPS29\t0\n+s_61529\tVWA5A\t0\n+s_61531\tVWA5A\t0\n+s_61587\tWBP1\t0\n+s_61595\tWBP2\t0\n+s_61623\tWDFY1\t0\n+s_61640\tWDHD1\t0\n+s_61662\tWDR16\t0\n+s_61695\tWDR26\t0\n+s_61739\tWDR44\t0\n+s_6200\tC11orf49\t0\n+s_62019\tWISP1\t0\n+s_62098\tWNT5B\t0\n+s_62114\tWNT8A\t0\n+s_62171\tWTAP\t0\n+s_62249\tXKR3\t0\n+s_62257\tXKR6\t0\n+s_62275\tXPC\t0\n+s_62320\tXRCC4\t0\n+s_62361\tYAE1D1\t0\n+s_62550\tZBBX\t0\n+s_62559\tZBED6\t0\n+s_62567\tZBTB1\t0\n+s_62624\tZBTB37\t0\n+s_62657\tZBTB47\t0\n+s_62759\tZC3H7A\t0\n+s_62845\tZDHHC11\t0\n+s_62862\tZDHHC16\t0\n+s_62881\tZDHHC2\t0\n+s_6292\tC12orf23\t0\n+s_62975\tZFC3H1\t0\n+s_63034\tZFP64\t0\n+s_63104\tZFYVE27\t0\n+s_63107\tZFYVE27\t0\n+s_63114\tZFYVE28\t0\n+s_63217\tZMIZ2\t0\n+s_63228\tZMYM3\t0\n+s_63234\tZMYM3\t0\n+s_6326\tC12orf49\t0\n+s_63302\tZNF132\t0\n+s_63362\tZNF167\t0\n+s_63435\tZNF200\t0\n+s_63487\tZNF223\t0\n+s_63594\tZNF276\t0\n+s_636\tACO1\t0\n+s_63746\tZNF354B\t0\n+s_63755\tZNF362\t0\n+s_6376\tC12orf74\t0\n+s_63903\tZNF436\t0\n+s_63905\tZNF438\t0\n+s_63923\tZNF442\t0\n+s_63934\tZNF445\t0\n+s_63935\tZNF446\t0\n+s_63964\tZNF469\t0\n+s_63983\tZNF480\t0\n+s_6409\tC14orf105\t0\n+s_64137\tZNF554\t0\n+s_64241\tZNF586\t0\n+s_6427\tC14orf133\t0\n+s_64356\tZNF639\t0\n+s_64393\tZNF655\t0\n+s_64396\tZNF655\t0\n+s_64419\tZNF668\t0\n+s_64424\tZNF669\t0\n+s_64459\tZNF682\t0\n+s_64479\tZNF688\t0\n+s_64581\tZNF746\t0\n+s_64627\tZNF772\t0\n+s_64638\tZNF776\t0\n+s_64652\tZNF780A\t0\n+s_64791\tZNF85\t0\n+s_64851\tZNRF3\t0\n+s_64871\tZPBP\t0\n+s_64878\tZPLD1\t0\n+s_64898\tZSCAN10\t0\n+s_64930\tZSCAN30\t0\n+s_64997\tZYG11A\t0\n+s_6525\tC15orf39\t0\n+s_6592\tC16orf13\t0\n+s_6639\tC16orf62\t0\n+s_6707\tC17orf102\t0\n+s_6710\tC17orf104\t0\n+s_6728\tC17orf112\t0\n+s_6736\tC17orf39\t0\n+s_6794\tC17orf72\t0\n+s_6814\tC17orf80\t0\n+s_6849\tC18orf21\t0\n+s_6859\tC18orf32\t0\n+s_6862\tC18orf34\t0\n+s_6906\tC19orf38\t0\n+s_7053\tC1QTNF7\t0\n+s_7128\tC1orf122\t0\n+s_7144\tC1orf130\t0\n+s_7162\tC1orf144\t0\n+s_7234\tC1orf198\t0\n+s_7341\tC1orf63\t0\n+s_747\tACSL1\t0\n+s_76\tAARS2\t0\n+s_7674\tC2orf57\t0\n+s_7681\tC2orf62\t0\n+s_7692\tC2orf63\t0\n+s_77\tAARSD1\t0\n+s_78\tAARSD1\t0\n+s_781\tACSS1\t0\n+s_786\tACSS2\t0\n+s_7940\tC4orf26\t0\n+s_7970\tC4orf37\t0\n+s_8000\tC4orf52\t0\n+s_804\tACTB\t0\n+s_8073\tC5orf51\t0\n+s_8141\tC6orf162\t0\n+s_8227\tC7orf10\t0\n+s_8281\tC7orf59\t0\n+s_8318\tC8A\t0\n+s_8403\tC9orf100\t0\n+s_8470\tC9orf24\t0\n+s_8699\tCACNA1G\t0\n+s_8705\tCACNA1I\t0\n+s_871\tACTR8\t0\n+s_874\tACTR8\t0\n+s_8757\tCACNG5\t0\n+s_8797\tCADPS\t0\n+s_8879\tCALR\t0\n+s_8910\tCAMK2B\t0\n+s_893\tACVR1B\t0\n+s_8930\tCAMKK1\t0\n+s_8954\tCAMSAP1\t0\n+s_9064\tCAPRIN1\t0\n+s_9077\tCAPSL\t0\n+s_9109\tCARD17\t0\n+s_913\tACY1\t0\n+s_9171\tCASD1\t0\n+s_9196\tCASP10\t0\n+s_9285\tCATSPER3\t0\n+s_9506\tCCDC120\t0\n+s_9507\tCCDC121\t0\n+s_952\tADAM12\t0\n+s_9584\tCCDC149\t0\n+s_964\tADAM18\t0\n+s_9646\tCCDC170\t0\n+s_9710\tCCDC40\t0\n+s_9732\tCCDC48\t0\n+s_976\tADAM21\t0\n+s_9763\tCCDC62\t0\n+s_9868\tCCDC89\t0\n+s_991\tADAM30\t0\n+s_9925\tCCL1\t0\n+s_9973\tCCL26\t0\n' |
| b |
| diff -r 80cf607159ae -r 82a180e6b582 test-data/out.test.R --- a/test-data/out.test.R Sat Feb 17 10:41:13 2018 -0500 +++ b/test-data/out.test.R Wed Apr 04 11:03:05 2018 -0400 |
| [ |
| b'@@ -10,7 +10,7 @@\n # outputfile=\'__OUTPUT_FILE__\'\n targetgenelist=c("ACIN1","ACTR8","AHCY","ACLY","AATF","AGBL5","AHCTF1","ABT1","ADIRF","ABCF1")\n # samplelabel=sub(\'.\\\\w+.\\\\w+$\',\'\',colnames(gstable)[startindex]);\n-samplelabel=\'HL60.final,KBM7.final_vs_HL60.initial,KBM7.initial neg.\'\n+samplelabel=\'HL60_final,KBM7_final_vs_HL60_initial,KBM7_initial neg.\'\n \n \n # You need to write some codes in front of this code:\n@@ -116,7 +116,7 @@\n # Do not modify the variables beginning with "__"\n targetmat=list(c(561.4907165816957,824.0396348113272,428.37415340969943,579.047491896501),c(3424.79939695118,3818.2871009576584,1992.3498917052,690.0506672205338),c(846.6456878299913,985.6508562937211,335.0024675413113,415.97581680707134),c(2432.636481525409,2122.257249136931,1067.465489792653,155.6333179800872),c(1308.1851773762019,2186.1913587343615,1482.5909580453515,997.3120339679854),c(405.68439208520414,268.16807081144486,170.34023773287015,109.85881269182627),c(640.8637498157573,559.4234589775174,711.6436598617687,632.2603542941043),c(946.5969148654764,470.6260845366416,663.0651476194316,457.74505288260946),c(246.9383256170808,177.59474888175154,28.39003962214503,0.0),c(568.8400715107754,612.7018836420428,564.0154538266146,270.64176251684285))\n targetgene="ACIN1"\n-collabel=c("HL60.initial","KBM7.initial","HL60.final","KBM7.final")\n+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")\n \n # set up color using RColorBrewer\n #library(RColorBrewer)\n@@ -151,7 +151,7 @@\n # Do not modify the variables beginning with "__"\n targetmat=list(c(2484.0819660289676,2349.578527705573,2172.7843657481662,910.9126552363929),c(992.1629154257711,1005.1862786707138,743.8190381001997,200.26346063614164),c(1267.0287897733551,1156.1418152202027,251.09412821363824,42.34141739164138),c(1500.738276518092,1315.977089213779,800.5991173444897,1476.2277955464156),c(1925.5309914189038,2054.7712445618654,194.94493873872918,235.16652091844063),c(351.29916561001374,781.4168950797068,227.75120674654121,624.2498158686586),c(1719.74905340467,1006.9622261595313,356.45271970026533,222.0063506480656),c(903.9706562768137,1445.6212558974576,1482.5909580453515,1055.1023468944147),c(651.152846716469,1081.552020689867,576.0023594448536,1072.2677863775127),c(285.1549712482957,408.46792242802854,99.0496937928171,44.630142656054424))\n targetgene="ACTR8"\n-collabel=c("HL60.initial","KBM7.initial","HL60.final","KBM7.final")\n+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")\n \n # set up color using RColorBrewer\n #library(RColorBrewer)\n@@ -186,7 +186,7 @@\n # Do not modify the variables beginning with "__"\n targetmat=list(c(301.3235520922712,657.1005708624807,228.38209651592223,137.32351586478285),c(1142.0897559789987,1099.311495578042,112.92926871919911,100.70391163417409),c(789.3207193831689,671.3081507730209,723.6305654800077,588.7745742702564),c(392.45555321286054,412.0198174056636,334.37157777193033,213.99581222261992),c(2009.3136376104133,2235.917888421252,2437.1271791188055,1937.9781176417478),c(1071.5359486598327,406.69197493921104,645.4002340767636,349.602784139093),c(61.7345814042702,218.44154112455442,614.4866353770946,452.5954210376801),c(651.152846716469,879.0940069646701,237.21455328725622,18.88198343140764),c(1625.6773103124485,1410.1023061211074,2146.286995434164,1986.613529510525),c(1053.8974968300413,882.6459019423052,106.6203710253891,105.85354347910344))\n targetgene="AHCY"\n-collabel=c("HL60.initial","KBM7.initial","HL60.final","KBM7.final")\n+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")\n \n # set up color using RColorBrewer\n #library(RColorBrewer)\n@@ -221,7 +221,7 @@\n # Do not modify the variables beginning with "__"\n targetmat=list(c(1268.498660759171,1411.8782536099247,1136.2324746551822,603.6512884889412),c(327.78122983695846,454.642557137284,51.73296108924205,24.031615276336996),c(132.28838872343613,241.5288584791821,123.02350502929512,65.80085135187511),c(495.34652221997754,586.0626713097802,279.4841678357833,243.749240'..b'748304,1296.4784760779562,1222.1792911965672),c(1193.5352404825571,1355.0479339677643,1622.0175970785526,1905.9359639399652),c(868.6937526172306,701.4992580829187,720.4761166331027,603.6512884889412),c(798.1399452980647,768.9852626579842,1478.8056194290655,1756.0244591209105),c(1168.5474337236858,907.5091667857504,879.4603385171149,977.8578692204745),c(809.8989131845924,687.2916781723785,678.8373918539567,865.7103312642352),c(1246.4505959719315,753.0017352586266,1301.5255942330043,1264.5207085882087),c(826.0674940285679,797.4004224790644,977.8791425405509,2066.7189137649816))\n targetgene="ADCK1"\n-collabel=c("HL60.initial","KBM7.initial","HL60.final","KBM7.final")\n+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")\n \n # set up color using RColorBrewer\n #library(RColorBrewer)\n@@ -822,7 +822,7 @@\n # Do not modify the variables beginning with "__"\n targetmat=list(c(1863.7964100146337,1585.9211075140413,1761.4442361117538,1464.211987908247),c(742.2848478370584,598.4943037315028,943.8110949939769,820.5080072920774),c(1568.3523418656262,2083.1864043829455,1810.6536381234716,1887.6261618246608),c(1018.6205931704583,513.248824268262,679.4682816233377,824.5132765048003),c(1140.6198849931827,1191.6607649965529,880.0912282864958,977.8578692204745),c(135.22813069506805,118.98848175077354,351.40560154521734,399.95473995618005),c(665.8515565746286,701.4992580829187,986.7115993118849,746.6966175147567),c(418.9132309575478,300.1351256101601,376.6411923204574,645.4205245644794),c(561.4907165816957,543.4399315781598,881.9838975946388,580.7640358448108),c(442.4311667306031,229.0972260574595,395.5678854018874,651.142337725512))\n targetgene="ADARB2"\n-collabel=c("HL60.initial","KBM7.initial","HL60.final","KBM7.final")\n+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")\n \n # set up color using RColorBrewer\n #library(RColorBrewer)\n@@ -857,7 +857,7 @@\n # Do not modify the variables beginning with "__"\n targetmat=list(c(734.9354929079785,358.74139274113816,541.9343118982795,378.7840312603593),c(595.2977492554626,591.3905137762326,1061.787481868224,887.4532212761591),c(1655.0747300287676,943.0281165621008,1069.358159100796,2038.1098479598186),c(626.1650399575977,884.4218494311227,517.3296108924205,858.2719741548927),c(680.5502664327881,747.673892792174,533.1018551269456,1016.194017399393),c(662.9118146029966,777.8650001020718,864.9498738213518,787.3214909580882),c(880.4527205037583,621.5816210861304,671.8976043907657,1040.7978139918332),c(94.07174309222125,447.5387671820139,711.6436598617687,927.5059134033875),c(399.80490814194036,806.280159923152,1147.58849050404,1059.1076161071376),c(698.1887182625796,531.0082991564371,504.0809257354195,347.8862401907832))\n targetgene="ACSS2"\n-collabel=c("HL60.initial","KBM7.initial","HL60.final","KBM7.final")\n+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")\n \n # set up color using RColorBrewer\n #library(RColorBrewer)\n@@ -892,7 +892,7 @@\n # Do not modify the variables beginning with "__"\n targetmat=list(c(408.62413405683606,523.9045092011671,483.89245311522745,701.494293542599),c(1805.0015705819953,1434.9655709645526,1712.2348341000356,2152.546111180471),c(3017.64513388016,2642.609863360463,1834.6274493599499,3573.2723190648703),c(1649.1952460855039,783.1928425685244,773.4708572611067,1332.0381038883936),c(959.82575373782,1397.6706736993847,1429.5962174173474,2811.126806015325),c(495.34652221997754,301.9110730989776,336.89513684945433,555.015876620164),c(1491.9190506031964,1331.9606166131366,2087.614246881731,1983.1804416139055),c(429.2023278582595,889.7496918975753,567.8007924429005,1132.9190058844583),c(427.7324568724435,573.6310388880576,655.4944703868597,899.4690289143276),c(690.8393633334998,767.2093151691668,1040.33722970927,993.3067647552625))\n targetgene="ADNP"\n-collabel=c("HL60.initial","KBM7.initial","HL60.final","KBM7.final")\n+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")\n \n # set up color using RColorBrewer\n #library(RColorBrewer)\n' |
| b |
| diff -r 80cf607159ae -r 82a180e6b582 test-data/out.test.log.txt --- a/test-data/out.test.log.txt Sat Feb 17 10:41:13 2018 -0500 +++ b/test-data/out.test.log.txt Wed Apr 04 11:03:05 2018 -0400 |
| b |
| b'@@ -1,112 +1,109 @@\n-INFO @ Mon, 12 Feb 2018 03:40:01: Parameters: /home/maria/miniconda3/envs/mulled-v1-b1e6893952d2d7e4d51a13d040adcd7bea052bfdc57a24d59056014db875e749/bin/mageck test -k /tmp/tmp0xS0Jl/files/000/dataset_21.dat -t HL60.final,KBM7.final -c HL60.initial,KBM7.initial -n output --normcounts-to-file --pdf-report --norm-method median --gene-test-fdr-threshold 0.25 --adjust-method fdr --sort-criteria neg --remove-zero none --gene-lfc-method median \n-INFO @ Mon, 12 Feb 2018 03:40:01: Welcome to MAGeCK v0.5.7. Command: test \n-INFO @ Mon, 12 Feb 2018 03:40:01: Loading count table from /tmp/tmp0xS0Jl/files/000/dataset_21.dat \n-INFO @ Mon, 12 Feb 2018 03:40:01: Processing 1 lines.. \n-DEBUG @ Mon, 12 Feb 2018 03:40:01: Parsing error in line 1 (usually the header line). Skip this line. \n-INFO @ Mon, 12 Feb 2018 03:40:01: Loaded 999 records. \n-INFO @ Mon, 12 Feb 2018 03:40:01: Loading R template file: /home/maria/miniconda3/envs/mulled-v1-b1e6893952d2d7e4d51a13d040adcd7bea052bfdc57a24d59056014db875e749/lib/python3.6/site-packages/mageck/plot_template.RTemplate. \n-INFO @ Mon, 12 Feb 2018 03:40:01: Loading R template file: /home/maria/miniconda3/envs/mulled-v1-b1e6893952d2d7e4d51a13d040adcd7bea052bfdc57a24d59056014db875e749/lib/python3.6/site-packages/mageck/plot_template_indvgene.RTemplate. \n-INFO @ Mon, 12 Feb 2018 03:40:01: Loading Rnw template file: /home/maria/miniconda3/envs/mulled-v1-b1e6893952d2d7e4d51a13d040adcd7bea052bfdc57a24d59056014db875e749/lib/python3.6/site-packages/mageck/plot_template.Rnw. \n-DEBUG @ Mon, 12 Feb 2018 03:40:01: Setting up the visualization module... \n-DEBUG @ Mon, 12 Feb 2018 03:40:01: Given sample labels: HL60.final,KBM7.final \n-DEBUG @ Mon, 12 Feb 2018 03:40:01: Converted index: 2 3 \n-INFO @ Mon, 12 Feb 2018 03:40:01: Treatment samples:HL60.final,KBM7.final \n-INFO @ Mon, 12 Feb 2018 03:40:01: Treatment sample index:2,3 \n-DEBUG @ Mon, 12 Feb 2018 03:40:01: Given sample labels: HL60.initial,KBM7.initial \n-DEBUG @ Mon, 12 Feb 2018 03:40:01: Converted index: 0 1 \n-INFO @ Mon, 12 Feb 2018 03:40:01: Control samples:HL60.initial,KBM7.initial \n-INFO @ Mon, 12 Feb 2018 03:40:01: Control sample index:0,1 \n-DEBUG @ Mon, 12 Feb 2018 03:40:01: Initial (total) size factor: 1.6666455325878438 2.027372749328462 0.7198064117880387 0.6589869375844738 \n-DEBUG @ Mon, 12 Feb 2018 03:40:01: Median factor: 1.469870985815957 1.7759474888175155 0.6308897693810006 0.5721813161032618 \n-INFO @ Mon, 12 Feb 2018 03:40:01: Final size factor: 1.469870985815957 1.7759474888175155 0.6308897693810006 0.5721813161032618 \n-INFO @ Mon, 12 Feb 2018 03:40:01: Writing normalized read counts to output.normalized.txt \n-DEBUG @ Mon, 12 Feb 2018 03:40:01: Adjusted model: 1.1175084644498339\t3.4299551007579927 \n-INFO @ Mon, 12 Feb 2018 03:40:01: Raw variance calculation: 0.5 for control, 0.5 for treatment \n-INFO @ Mon, 12 Feb 2018 03:40:01: Adjusted variance calculation: 0.3333333333333333 for raw variance, 0.6666666666666667 for modeling \n-INFO @ Mon, 12 Feb 2018 03:40:01: Use qnorm to reversely calculate sgRNA scores ... \n-DEBUG @ Mon, 12 Feb 2018 03:40:01: lower test FDR cutoff: 0.3283283283283283 \n-DEBUG @ Mon, 12 Feb 2018 03:40:01: higher test FDR cutoff: 0.34534534534534533 \n-INFO @ Mon, 12 Feb 2018 03:40:01: Running command: RRA -i output.plow.txt -o output.gene.low.txt -p 0.3283283283283283 --skip-gene NA --skip-gene na \n-INFO @ Mon, 12 Feb 2018 03:40:02: Command message: \n-INFO @ Mon, 12 Feb 2018 03:40:02: Welcome to RRA v 0.5.7. \n-INFO @ Mon, 12 Feb 2018 03:40:02: Skipping gene NA for permutation ... \n-INFO @ Mon, 12 Feb 2018 03:40:02: Skipping gene na for permutation ... \n-INFO @ Mon, 12 Feb 2018 03:40:02: Reading input file... \n-INFO @ Mon, 12 Feb 2018 03:40:02: Summary: 999 sgRNAs, 100 genes, 1 lists; skipped sgRNAs:0 \n-INFO @ Mon, 12 Feb 2018 03:40:02: Computing lo-values for each group... \n-INFO @ Mon, 12 Feb 2018 03:40:02: Computing false discovery rate... \n-INFO @ Mon, 12 Feb 2'..b'+INFO @ Mon, 26 Mar 2018 08:37:53: Permuting genes with 9 sgRNAs... \n+INFO @ Mon, 26 Mar 2018 08:37:53: Permuting genes with 10 sgRNAs... \n+INFO @ Mon, 26 Mar 2018 08:37:53: Number of genes under FDR adjustment: 100 \n+INFO @ Mon, 26 Mar 2018 08:37:53: Saving to output file... \n+INFO @ Mon, 26 Mar 2018 08:37:53: RRA completed. \n+INFO @ Mon, 26 Mar 2018 08:37:53: \n+INFO @ Mon, 26 Mar 2018 08:37:53: End command message. \n+DEBUG @ Mon, 26 Mar 2018 08:37:53: Sorting the merged items by negative selection... \n+INFO @ Mon, 26 Mar 2018 08:37:53: Loading top 10 genes from output.gene.low.txt: ACIN1,ACTR8,AHCY,ACLY,AATF,AGBL5,AHCTF1,ABT1,ADIRF,ABCF1 \n+DEBUG @ Mon, 26 Mar 2018 08:37:53: Column index:3 \n+INFO @ Mon, 26 Mar 2018 08:37:53: Loading top 10 genes from output.gene.high.txt: ACRC,AGAP3,ADCK4,AHRR,ADRBK1,ADK,ADCK1,ADARB2,ACSS2,ADNP \n+DEBUG @ Mon, 26 Mar 2018 08:37:53: Column index:9 \n+INFO @ Mon, 26 Mar 2018 08:37:53: Running command: rm output.plow.txt \n+INFO @ Mon, 26 Mar 2018 08:37:53: Running command: rm output.phigh.txt \n+INFO @ Mon, 26 Mar 2018 08:37:54: Running command: rm output.gene.low.txt \n+INFO @ Mon, 26 Mar 2018 08:37:54: Running command: rm output.gene.high.txt \n+INFO @ Mon, 26 Mar 2018 08:37:54: Running command: cd ./; Rscript output.R \n+INFO @ Mon, 26 Mar 2018 08:37:59: Command message: \n+INFO @ Mon, 26 Mar 2018 08:37:59: null device \n+INFO @ Mon, 26 Mar 2018 08:37:59: 1 \n+INFO @ Mon, 26 Mar 2018 08:37:59: Writing to file output_summary.tex \n+INFO @ Mon, 26 Mar 2018 08:37:59: Processing code chunks with options ... \n+INFO @ Mon, 26 Mar 2018 08:37:59: 1 : keep.source term verbatim (label = funcdef, output_summary.Rnw:27) \n+INFO @ Mon, 26 Mar 2018 08:37:59: 2 : keep.source term tex (label = tab1, output_summary.Rnw:37) \n+INFO @ Mon, 26 Mar 2018 08:37:59: 3 : keep.source term verbatim (output_summary.Rnw:77) \n+INFO @ Mon, 26 Mar 2018 08:37:59: 4 : keep.source term verbatim pdf (output_summary.Rnw:83) \n+INFO @ Mon, 26 Mar 2018 08:37:59: 5 : keep.source term verbatim pdf (output_summary.Rnw:201) \n+INFO @ Mon, 26 Mar 2018 08:37:59: 6 : keep.source term verbatim pdf (output_summary.Rnw:345) \n+INFO @ Mon, 26 Mar 2018 08:37:59: 7 : keep.source term verbatim pdf (output_summary.Rnw:489) \n+INFO @ Mon, 26 Mar 2018 08:37:59: 8 : keep.source term verbatim (output_summary.Rnw:567) \n+INFO @ Mon, 26 Mar 2018 08:37:59: 9 : keep.source term verbatim pdf (output_summary.Rnw:573) \n+INFO @ Mon, 26 Mar 2018 08:37:59: 10 : keep.source term verbatim pdf (output_summary.Rnw:691) \n+INFO @ Mon, 26 Mar 2018 08:37:59: 11 : keep.source term verbatim pdf (output_summary.Rnw:835) \n+INFO @ Mon, 26 Mar 2018 08:37:59: 12 : keep.source term verbatim pdf (output_summary.Rnw:979) \n+INFO @ Mon, 26 Mar 2018 08:37:59: \n+INFO @ Mon, 26 Mar 2018 08:37:59: You can now run (pdf)latex on \xe2\x80\x98output_summary.tex\xe2\x80\x99 \n+INFO @ Mon, 26 Mar 2018 08:37:59: \n+INFO @ Mon, 26 Mar 2018 08:37:59: End command message. \n+INFO @ Mon, 26 Mar 2018 08:37:59: Running command: cd ./; rm -rf output_summary-*.pdf \n+INFO @ Mon, 26 Mar 2018 08:37:59: Command message: \n+INFO @ Mon, 26 Mar 2018 08:37:59: \n+INFO @ Mon, 26 Mar 2018 08:37:59: End command message. \n+INFO @ Mon, 26 Mar 2018 08:37:59: Running command: cd ./; rm -rf output_summary.aux \n+INFO @ Mon, 26 Mar 2018 08:37:59: Command message: \n+INFO @ Mon, 26 Mar 2018 08:37:59: \n+INFO @ Mon, 26 Mar 2018 08:37:59: End command message. \n+INFO @ Mon, 26 Mar 2018 08:37:59: Running command: cd ./; rm -rf output_summary.tex \n+INFO @ Mon, 26 Mar 2018 08:37:59: Command message: \n+INFO @ Mon, 26 Mar 2018 08:37:59: \n+INFO @ Mon, 26 Mar 2018 08:37:59: End command message. \n+INFO @ Mon, 26 Mar 2018 08:37:59: Running command: cd ./; rm -rf output_summary.toc \n+INFO @ Mon, 26 Mar 2018 08:37:59: Command message: \n+INFO @ Mon, 26 Mar 2018 08:37:59: \n+INFO @ Mon, 26 Mar 2018 08:37:59: End command message. \n' |
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| diff -r 80cf607159ae -r 82a180e6b582 test-data/out.test.normalized.txt --- a/test-data/out.test.normalized.txt Sat Feb 17 10:41:13 2018 -0500 +++ b/test-data/out.test.normalized.txt Wed Apr 04 11:03:05 2018 -0400 |
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| @@ -1,4 +1,4 @@ -sgRNA Gene HL60.initial KBM7.initial HL60.final KBM7.final +sgRNA Gene HL60_initial KBM7_initial HL60_final KBM7_final A1CF_m52595977 A1CF 313.08251997879887 486.6096119359992 557.0756663634236 100.13173031807082 A1CF_m52596017 A1CF 432.1420698298914 731.6903653928164 980.402701618075 1081.994868751268 A1CF_m52596056 A1CF 618.8156850285179 653.5486758848457 357.0836094696463 434.28561892237576 |
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| diff -r 80cf607159ae -r 82a180e6b582 test-data/out.test.report.pdf |
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| diff -r 80cf607159ae -r 82a180e6b582 test-data/output.count_normalized.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/output.count_normalized.txt Wed Apr 04 11:03:05 2018 -0400 |
| b |
| b'@@ -0,0 +1,2551 @@\n+sgRNA\tGene\ttest1_fastq_gz\n+s_47512\tRNF111\t2.0\n+s_24835\tHCFC1R1\t2.0\n+s_14784\tCYP4B1\t8.0\n+s_51146\tSLC18A1\t2.0\n+s_58960\tTRIM5\t2.0\n+s_48256\tRPRD2\t2.0\n+s_30297\tKRTAP5-5\t2.0\n+s_14555\tCYB5B\t2.0\n+s_39959\tPAAF1\t2.0\n+s_45293\tPUF60\t2.0\n+s_49358\tSCN8A\t2.0\n+s_64995\tZYG11A\t2.0\n+s_4029\tASTE1\t2.0\n+s_45554\tR3HDML\t2.0\n+s_34264\tMMRN1\t2.0\n+s_37459\tNOL6\t2.0\n+s_23990\tGPX7\t2.0\n+s_20268\tFANCC\t2.0\n+s_14157\tCTLA4\t2.0\n+s_36773\tNEURL4\t36.0\n+s_18804\tETFB\t2.0\n+s_782\tACSS1\t2.0\n+s_18272\tENPP2\t2.0\n+s_46620\tRCN1\t2.0\n+s_55436\tTAS2R3\t2.0\n+s_57947\tTMPRSS2\t2.0\n+s_6438\tC14orf159\t2.0\n+s_33846\tMGST2\t2.0\n+s_16328\tDNAH6\t2.0\n+s_17875\tEIF4G1\t2.0\n+s_2305\tANAPC11\t2.0\n+s_2500\tANKRD2\t2.0\n+s_82\tAARSD1\t2.0\n+s_55329\tTAL1\t2.0\n+s_57926\tTMPRSS11E\t16.0\n+s_38414\tNUP98\t8.0\n+s_50044\tSERPINF1\t2.0\n+s_9257\tCASR\t2.0\n+s_63396\tZNF182\t2.0\n+s_56478\tTHBS3\t2.0\n+s_17191\tDYRK1A\t2.0\n+s_11988\tCIR1\t2.0\n+s_43313\tPPARD\t2.0\n+s_44681\tPSMA4\t2.0\n+s_10387\tCD320\t2.0\n+s_64869\tZPBP\t2.0\n+s_54385\tSTK17B\t2.0\n+s_25423\tHIST1H4D\t2.0\n+s_54172\tST8SIA4\t18.0\n+s_1161\tADCY10\t2.0\n+s_29184\tKIAA0913\t2.0\n+s_42977\tPOLD3\t2.0\n+s_49449\tSCUBE1\t2.0\n+s_24181\tGRM4\t2.0\n+s_52507\tSMARCA5\t2.0\n+s_28674\tKCNJ10\t2.0\n+s_61074\tVAMP2\t8.0\n+s_3954\tASIC2\t2.0\n+s_2385\tANK1\t2.0\n+s_18397\tEPDR1\t2.0\n+s_18377\tEPB41L4B\t2.0\n+s_34580\tMRAP2\t2.0\n+s_48676\tRUFY3\t20.0\n+s_691\tACP1\t2.0\n+s_30460\tLAMP2\t2.0\n+s_42637\tPLRG1\t2.0\n+s_12695\tCNOT6\t2.0\n+s_33316\tMECOM\t4.0\n+s_35081\tMSRB2\t2.0\n+s_58512\tTPD52L2\t2.0\n+s_19912\tFAM22F\t2.0\n+s_45517\tQSOX2\t2.0\n+s_56705\tTINAG\t2.0\n+s_10946\tCDKL5\t2.0\n+s_57473\tTMEM211\t4.0\n+s_57657\tTMEM44\t2.0\n+s_43200\tPOT1\t2.0\n+s_19436\tFAM135A\t2.0\n+s_184\tABCB9\t2.0\n+s_30171\tKRT84\t2.0\n+s_44758\tPSMC3IP\t2.0\n+s_48313\tRPS3\t2.0\n+s_58142\tTNFSF12\t12.0\n+s_59718\tTTLL6\t14.0\n+s_9725\tCCDC43\t2.0\n+s_5135\tBCKDHA\t2.0\n+s_36539\tNDUFC2\t2.0\n+s_27251\tIL27RA\t2.0\n+s_48939\tSAMD10\t2.0\n+s_27343\tIL5RA\t2.0\n+s_28386\tKANK2\t2.0\n+s_27610\tINSRR\t2.0\n+s_2769\tAOC3\t4.0\n+s_58632\tTRA2B\t24.0\n+s_6674\tC16orf86\t2.0\n+s_22902\tGJD4\t2.0\n+s_48278\tRPS15A\t2.0\n+s_61998\tWIPF2\t2.0\n+s_4937\tBAIAP3\t4.0\n+s_54471\tSTOML1\t4.0\n+s_19157\tFABP12\t2.0\n+s_5434\tBIN1\t4.0\n+s_42042\tPIP5K1A\t2.0\n+s_7794\tC3orf18\t2.0\n+s_54846\tSVIL\t2.0\n+s_62273\tXPA\t2.0\n+s_45859\tRACGAP1\t2.0\n+s_53626\tSPOCK3\t2.0\n+s_43295\tPPAP2C\t14.0\n+s_11788\tCHRDL1\t4.0\n+s_50636\tSHQ1\t2.0\n+s_16705\tDPF1\t2.0\n+s_39741\tOTOF\t2.0\n+s_27505\tINHBE\t2.0\n+s_707\tACPL2\t2.0\n+s_15418\tDDX3Y\t12.0\n+s_56018\tTEAD4\t2.0\n+s_44367\tPRR12\t2.0\n+s_25875\tHOXB5\t2.0\n+s_49360\tSCN9A\t2.0\n+s_16244\tDMPK\t2.0\n+s_3909\tASCC2\t2.0\n+s_55088\tSYT6\t2.0\n+s_54311\tSTAU1\t2.0\n+s_53890\tSRP72\t2.0\n+s_11035\tCDX1\t2.0\n+s_18178\tEMR3\t4.0\n+s_16084\tDLD\t2.0\n+s_47207\tRHOBTB1\t2.0\n+s_40267\tPARK2\t12.0\n+s_43104\tPOLR3B\t2.0\n+s_2200\tAMDHD2\t2.0\n+s_12738\tCNRIP1\t2.0\n+s_17842\tEIF4A3\t2.0\n+s_57950\tTMPRSS3\t2.0\n+s_62146\tWRN\t2.0\n+s_11055\tCEACAM1\t2.0\n+s_54580\tSTX2\t2.0\n+s_29277\tKIAA1407\t2.0\n+s_33428\tMEF2A\t2.0\n+s_59797\tTUBB\t2.0\n+s_18113\tEME1\t2.0\n+s_29839\tKLHL8\t2.0\n+s_18058\tELP2\t2.0\n+s_49497\tSDCBP2\t6.0\n+s_16874\tDRP2\t2.0\n+s_13572\tCREBL2\t2.0\n+s_20540\tFBXO30\t2.0\n+s_64380\tZNF646\t2.0\n+s_50366\tSH2B1\t2.0\n+s_2548\tANKRD33B\t2.0\n+s_41183\tPDXP\t2.0\n+s_16315\tDNAH12\t2.0\n+s_19996\tFAM49B\t2.0\n+s_30751\tLDLRAD3\t2.0\n+s_36960\tNGEF\t2.0\n+s_39015\tOR2A2\t2.0\n+s_26302\tHSPB2\t2.0\n+s_64297\tZNF611\t10.0\n+s_730\tACSBG1\t2.0\n+s_50271\tSFXN4\t2.0\n+s_8592\tCA6\t4.0\n+s_13683\tCRMP1\t2.0\n+s_51103\tSLC16A7\t2.0\n+s_63785\tZNF384\t2.0\n+s_16339\tDNAH9\t2.0\n+s_55936\tTCTEX1D1\t2.0\n+s_14497\tCXorf40A\t2.0\n+s_1123\tADAT1\t2.0\n+s_41304\tPERP\t2.0\n+s_18719\tESAM\t2.0\n+s_35118\tMSX2\t2.0\n+s_30128\tKRT6A\t2.0\n+s_402\tABTB1\t2.0\n+s_32578\tMAP1LC3A\t2.0\n+s_45063\tPTMA\t2.0\n+s_43551\tPPP1R14D\t2.0\n+s_2538\tANKRD32\t2.0\n+s_40384\tPAX1\t2.0\n+s_29076\tKIAA0101\t2.0\n+s_40482\tPCDH10\t2.0\n+s_2348\tANGPT2\t2.0\n+s_59756\tTTYH3\t2.0\n+s_34330\tMOB4\t2.0\n+s_49331\tSCN2B\t2.0\n+s_54905\tSYDE1\t2.0\n+s_39101\tOR2T1\t2.0\n+s_36623\tNEDD4L\t2.0\n+s_40500\tPCDH15\t4.0\n+s_10660\tCDC42SE2\t2.0\n+s_30867\tLGALS13\t2.0\n+s_24322\tGSTK1\t4.0\n+s_59167\tTRPC1\t2.0\n+s_57440\tTMEM201\t2.0\n+s_50539\tSHC1\t2.0\n+s_37087\tNIT1\t2.0\n+s_56345\tTGFB2\t2.0\n+s_55388\tTARM1\t2.0\n+s_1224\tADD2\t2.0\n+s_5256\tBCOR\t4.0\n+s_51731\tSLC35B3\t2.0\n+s_12987\tCOL6A6\t2.0\n+s_56745\tTJP3\t2.0\n+s_19340\tFAM120AOS\t2.0\n+s_53904'..b'A\t0\n+s_57422\tTMEM198\t0\n+s_57429\tTMEM2\t0\n+s_57475\tTMEM212\t0\n+s_57531\tTMEM231\t0\n+s_57568\tTMEM245\t0\n+s_57700\tTMEM54\t0\n+s_57873\tTMF1\t0\n+s_57992\tTMUB1\t0\n+s_58180\tTNIP1\t0\n+s_58211\tTNKS2\t0\n+s_58237\tTNNT1\t0\n+s_58256\tTNPO2\t0\n+s_58259\tTNPO3\t0\n+s_58309\tTOM1\t0\n+s_58485\tTP73\t0\n+s_58503\tTPD52\t0\n+s_58533\tTPI1\t0\n+s_5857\tBSPRY\t0\n+s_58612\tTPSG1\t0\n+s_58633\tTRA2B\t0\n+s_58655\tTRAF3\t0\n+s_58668\tTRAF3IP2\t0\n+s_58690\tTRAK1\t0\n+s_58809\tTRIB2\t0\n+s_58962\tTRIM50\t0\n+s_58968\tTRIM52\t0\n+s_59050\tTRIO\t0\n+s_59107\tTRMT1L\t0\n+s_59133\tTRMT61B\t0\n+s_59160\tTROVE2\t0\n+s_59173\tTRPC4\t0\n+s_59196\tTRPM1\t0\n+s_59204\tTRPM3\t0\n+s_59311\tTSEN54\t0\n+s_59332\tTSHB\t0\n+s_59340\tTSHZ2\t0\n+s_59360\tTSNARE1\t0\n+s_5952\tBTG4\t0\n+s_59539\tTTC21A\t0\n+s_59602\tTTC39A\t0\n+s_59654\tTTC9C\t0\n+s_59717\tTTLL6\t0\n+s_5974\tBTN3A1\t0\n+s_59748\tTTYH1\t0\n+s_59807\tTUBB2B\t0\n+s_59859\tTULP1\t0\n+s_59870\tTULP3\t0\n+s_59955\tTXNDC8\t0\n+s_59983\tTXNRD2\t0\n+s_600\tACE\t0\n+s_60169\tUBE2H\t0\n+s_60209\tUBE2Q2\t0\n+s_60237\tUBE2V2\t0\n+s_60248\tUBE3A\t0\n+s_60250\tUBE3B\t0\n+s_60373\tUBXN6\t0\n+s_60396\tUCKL1\t0\n+s_60423\tUEVLD\t0\n+s_60438\tUFSP1\t0\n+s_60449\tUGDH\t0\n+s_60517\tUGT2A1\t0\n+s_60542\tUGT3A1\t0\n+s_60603\tUMODL1\t0\n+s_60614\tUNC119\t0\n+s_60649\tUNC5B\t0\n+s_6068\tC10orf125\t0\n+s_6071\tC10orf128\t0\n+s_60753\tUQCRC2\t0\n+s_60780\tURM1\t0\n+s_60839\tUSP15\t0\n+s_60851\tUSP19\t0\n+s_60925\tUSP4\t0\n+s_6100\tC10orf53\t0\n+s_6106\tC10orf54\t0\n+s_61149\tVAV2\t0\n+s_61173\tVCAM1\t0\n+s_61178\tVCAN\t0\n+s_61221\tVEPH1\t0\n+s_61263\tVIL1\t0\n+s_61341\tVPS13C\t0\n+s_61344\tVPS13D\t0\n+s_61367\tVPS29\t0\n+s_61529\tVWA5A\t0\n+s_61531\tVWA5A\t0\n+s_61587\tWBP1\t0\n+s_61595\tWBP2\t0\n+s_61623\tWDFY1\t0\n+s_61640\tWDHD1\t0\n+s_61662\tWDR16\t0\n+s_61695\tWDR26\t0\n+s_61739\tWDR44\t0\n+s_6200\tC11orf49\t0\n+s_62019\tWISP1\t0\n+s_62098\tWNT5B\t0\n+s_62114\tWNT8A\t0\n+s_62171\tWTAP\t0\n+s_62249\tXKR3\t0\n+s_62257\tXKR6\t0\n+s_62275\tXPC\t0\n+s_62320\tXRCC4\t0\n+s_62361\tYAE1D1\t0\n+s_62550\tZBBX\t0\n+s_62559\tZBED6\t0\n+s_62567\tZBTB1\t0\n+s_62624\tZBTB37\t0\n+s_62657\tZBTB47\t0\n+s_62759\tZC3H7A\t0\n+s_62845\tZDHHC11\t0\n+s_62862\tZDHHC16\t0\n+s_62881\tZDHHC2\t0\n+s_6292\tC12orf23\t0\n+s_62975\tZFC3H1\t0\n+s_63034\tZFP64\t0\n+s_63104\tZFYVE27\t0\n+s_63107\tZFYVE27\t0\n+s_63114\tZFYVE28\t0\n+s_63217\tZMIZ2\t0\n+s_63228\tZMYM3\t0\n+s_63234\tZMYM3\t0\n+s_6326\tC12orf49\t0\n+s_63302\tZNF132\t0\n+s_63362\tZNF167\t0\n+s_63435\tZNF200\t0\n+s_63487\tZNF223\t0\n+s_63594\tZNF276\t0\n+s_636\tACO1\t0\n+s_63746\tZNF354B\t0\n+s_63755\tZNF362\t0\n+s_6376\tC12orf74\t0\n+s_63903\tZNF436\t0\n+s_63905\tZNF438\t0\n+s_63923\tZNF442\t0\n+s_63934\tZNF445\t0\n+s_63935\tZNF446\t0\n+s_63964\tZNF469\t0\n+s_63983\tZNF480\t0\n+s_6409\tC14orf105\t0\n+s_64137\tZNF554\t0\n+s_64241\tZNF586\t0\n+s_6427\tC14orf133\t0\n+s_64356\tZNF639\t0\n+s_64393\tZNF655\t0\n+s_64396\tZNF655\t0\n+s_64419\tZNF668\t0\n+s_64424\tZNF669\t0\n+s_64459\tZNF682\t0\n+s_64479\tZNF688\t0\n+s_64581\tZNF746\t0\n+s_64627\tZNF772\t0\n+s_64638\tZNF776\t0\n+s_64652\tZNF780A\t0\n+s_64791\tZNF85\t0\n+s_64851\tZNRF3\t0\n+s_64871\tZPBP\t0\n+s_64878\tZPLD1\t0\n+s_64898\tZSCAN10\t0\n+s_64930\tZSCAN30\t0\n+s_64997\tZYG11A\t0\n+s_6525\tC15orf39\t0\n+s_6592\tC16orf13\t0\n+s_6639\tC16orf62\t0\n+s_6707\tC17orf102\t0\n+s_6710\tC17orf104\t0\n+s_6728\tC17orf112\t0\n+s_6736\tC17orf39\t0\n+s_6794\tC17orf72\t0\n+s_6814\tC17orf80\t0\n+s_6849\tC18orf21\t0\n+s_6859\tC18orf32\t0\n+s_6862\tC18orf34\t0\n+s_6906\tC19orf38\t0\n+s_7053\tC1QTNF7\t0\n+s_7128\tC1orf122\t0\n+s_7144\tC1orf130\t0\n+s_7162\tC1orf144\t0\n+s_7234\tC1orf198\t0\n+s_7341\tC1orf63\t0\n+s_747\tACSL1\t0\n+s_76\tAARS2\t0\n+s_7674\tC2orf57\t0\n+s_7681\tC2orf62\t0\n+s_7692\tC2orf63\t0\n+s_77\tAARSD1\t0\n+s_78\tAARSD1\t0\n+s_781\tACSS1\t0\n+s_786\tACSS2\t0\n+s_7940\tC4orf26\t0\n+s_7970\tC4orf37\t0\n+s_8000\tC4orf52\t0\n+s_804\tACTB\t0\n+s_8073\tC5orf51\t0\n+s_8141\tC6orf162\t0\n+s_8227\tC7orf10\t0\n+s_8281\tC7orf59\t0\n+s_8318\tC8A\t0\n+s_8403\tC9orf100\t0\n+s_8470\tC9orf24\t0\n+s_8699\tCACNA1G\t0\n+s_8705\tCACNA1I\t0\n+s_871\tACTR8\t0\n+s_874\tACTR8\t0\n+s_8757\tCACNG5\t0\n+s_8797\tCADPS\t0\n+s_8879\tCALR\t0\n+s_8910\tCAMK2B\t0\n+s_893\tACVR1B\t0\n+s_8930\tCAMKK1\t0\n+s_8954\tCAMSAP1\t0\n+s_9064\tCAPRIN1\t0\n+s_9077\tCAPSL\t0\n+s_9109\tCARD17\t0\n+s_913\tACY1\t0\n+s_9171\tCASD1\t0\n+s_9196\tCASP10\t0\n+s_9285\tCATSPER3\t0\n+s_9506\tCCDC120\t0\n+s_9507\tCCDC121\t0\n+s_952\tADAM12\t0\n+s_9584\tCCDC149\t0\n+s_964\tADAM18\t0\n+s_9646\tCCDC170\t0\n+s_9710\tCCDC40\t0\n+s_9732\tCCDC48\t0\n+s_976\tADAM21\t0\n+s_9763\tCCDC62\t0\n+s_9868\tCCDC89\t0\n+s_991\tADAM30\t0\n+s_9925\tCCL1\t0\n+s_9973\tCCL26\t0\n' |
| b |
| diff -r 80cf607159ae -r 82a180e6b582 test-data/output_countsummary.Rnw --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/output_countsummary.Rnw Wed Apr 04 11:03:05 2018 -0400 |
| [ |
| @@ -0,0 +1,237 @@ +% This is a template file for Sweave used in MAGeCK +% Author: Wei Li, Shirley Liu lab +% Do not modify lines beginning with "#__". +\documentclass{article} + +\usepackage{amsmath} +\usepackage{amscd} +\usepackage[tableposition=top]{caption} +\usepackage{ifthen} +\usepackage{fullpage} +\usepackage[utf8]{inputenc} +% \usepackage{longtable} + +\begin{document} +\setkeys{Gin}{width=0.9\textwidth} + +\title{MAGeCK Count Report} +\author{Wei Li} + +\maketitle + + +\tableofcontents + +\section{Summary} + +%Function definition +<<label=funcdef,include=FALSE,echo=FALSE>>= +genreporttable<-function(filelist,labellist,reads,mappedreads){ + xtb=data.frame(Label=labellist,Reads=reads,MappedReads=mappedreads,MappedPercentage=mappedreads/reads); + colnames(xtb)=c("Label","Reads","Mapped","Percentage"); + return (xtb); +} +genreporttable2<-function(filelist,labellist,sgrnas,zerocounts,gini){ + xtb=data.frame(Label=labellist,TotalsgRNAs=sgrnas,ZeroCounts=zerocounts,GiniIndex=gini); + colnames(xtb)=c("Label","TotalsgRNA","ZeroCounts","GiniIndex"); + return (xtb); +} +genreporttable3<-function(filelist,labellist){ + xtb=data.frame(File=filelist,Label=labellist); + colnames(xtb)=c("File","Label"); + return (xtb); +} + + +colors=c( "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#A65628", "#F781BF", + "#999999", "#66C2A5", "#FC8D62", "#8DA0CB", "#E78AC3", "#A6D854", "#FFD92F", "#E5C494", "#B3B3B3", + "#8DD3C7", "#FFFFB3", "#BEBADA", "#FB8072", "#80B1D3", "#FDB462", "#B3DE69", "#FCCDE5", + "#D9D9D9", "#BC80BD", "#CCEBC5", "#FFED6F"); + + + +genboxplot<-function(filename,...){ + #slmed=read.table(filename,header=T) + slmed=read.table(filename,header=T) + slmat=as.matrix(slmed[,c(-1,-2)]) + slmat_log=log2(slmat+1) + + boxplot(slmat_log,pch='.',las=2,ylab='log2(read counts)',cex.axis=0.8,...) +} + + +genhistplot<-function(filename,isfile=T,...){ + if(isfile){ + slmed=read.table(filename,header=T) + }else{ + slmed=filename; + } + tabsmat=as.matrix(log2(slmed[,c(-1,-2)]+1)) + colnames(tabsmat)=colnames(slmed)[c(-1,-2)] + samplecol=colors[((1:ncol(tabsmat)) %% length(colors)) ] + if(ncol(tabsmat)>=1){ + histlist=lapply(1:ncol(tabsmat),function(X){ return (hist(tabsmat[,X],plot=F,breaks=40)) }) + xrange=range(unlist(lapply(histlist,function(X){X$mids}))) + yrange=range(unlist(lapply(histlist,function(X){X$counts}))) + hst1=histlist[[1]] + plot(hst1$mids,hst1$counts,type='b',pch=20,xlim=c(0,xrange[2]*1.2),ylim=c(0,yrange[2]*1.2),xlab='log2(counts)',ylab='Frequency',main='Distribution of read counts',col = samplecol[1], ... ) + } + if(ncol(tabsmat)>=2){ + for(i in 2:ncol(tabsmat)){ + hstn=histlist[[i]] + lines(hstn$mids,hstn$counts,type='b',pch=20,col=samplecol[i]) + } + } + legend('topright',colnames(tabsmat),pch=20,lwd=1,col=samplecol) +} + + + +genclustering<-function(filename,...){ + #slmed=read.table(filename,header=T) + slmed=read.table(filename,header=T) + slmat=as.matrix(slmed[,c(-1,-2)]) + slmat_log=log2(slmat+1) + + result=tryCatch({ + library(gplots); + heatmap.2(cor(slmat_log),trace = 'none',density.info = 'none',cexRow = 0.8,cexCol = 0.8,offsetRow = -0.2,offsetCol = -0.2) + }, error=function(e){ + heatmap(cor(slmat_log),scale='none',cexRow = 0.8,cexCol = 0.8,cex.axis=0.8,...) + }); +} + +ctfit_tx=0; + + +panel.plot<-function(x,y,textnames=names(x),...){ + par(new=TRUE) + m<-cbind(x,y) + plot(m,pch=20,xlim = range(x)*1.1,ylim=range(y)*1.1,...) + text(x,y,textnames,...) +} + + +genpcaplot<-function(filename,...){ + #slmed=read.table(filename,header=T) + slmed=read.table(filename,header=T) + slmat=as.matrix(slmed[,c(-1,-2)]) + slmat_log=log2(slmat+1) + ctfit_tx<<-prcomp(t(slmat_log),center=TRUE) + + # par(mfrow=c(2,1)); + samplecol=colors[((1:ncol(slmat)) %% length(colors)) ] + # first 2 PCA + #plot(ctfit_tx$x[,1],ctfit_tx$x[,2],xlab='PC1',ylab='PC2',main='First 2 PCs',col=samplecol,xlim=1.1*range(ctfit_tx$x[,1]),ylim=1.1*range(ctfit_tx$x[,2])); + #text(ctfit_tx$x[,1],ctfit_tx$x[,2],rownames(ctfit_tx$x),col=samplecol); + # par(mfrow=c(1,1)); + if(length(samplecol)>2){ + pairs(ctfit_tx$x[,1:3],panel=panel.plot,textnames=rownames(ctfit_tx$x),main='First 3 principle components',col=samplecol) + }else{ + if(length(samplecol)>1){ + pairs(ctfit_tx$x[,1:2],panel=panel.plot,textnames=rownames(ctfit_tx$x),main='First 2 principle components',col=samplecol) + } + } + + +} + +genpcavar<-function(){ + # % variance + varpca=ctfit_tx$sdev^2 + varpca=varpca/sum(varpca)*100; + if(length(varpca)>10){ + varpca=varpca[1:10]; + } + plot(varpca,type='b',lwd=2,pch=20,xlab='PCs',ylab='% Variance explained'); +} + +@ + +%__FILE_SUMMARY__ + +The statistics of comparisons are listed in Table 1 and Table 2. +The corresponding fastq files in each row are listed in Table 3. + +<<label=tab1,echo=FALSE,results=tex>>= +library(xtable) +filelist=c("input_0.gz"); +labellist=c("test1_fastq_gz"); +reads=c(2500); +mappedreads=c(1453); +totalsgrnas=c(2550); +zerocounts=c(1276); +giniindex=c(0.5266899931488773); + +cptable=genreporttable(filelist,labellist,reads,mappedreads); +print(xtable(cptable, caption = "Summary of comparisons", label = "tab:one", + digits = c(0, 0, 0, 0,2), + align=c('c', 'c','c', 'c', 'c'), + table.placement = "tbp", + caption.placement = "top")) +@ + +<<label=tab2,echo=FALSE,results=tex>>= +library(xtable) +cptable=genreporttable2(filelist,labellist,totalsgrnas,zerocounts,giniindex); +print(xtable(cptable, caption = "Summary of comparisons", label = "tab:two", + digits = c(0, 0,0, 0,2), + align=c('c', 'c','c', 'c', 'c'), + table.placement = "tbp", + caption.placement = "top")) +@ + + + + + +<<label=tab3,echo=FALSE,results=tex>>= +library(xtable) +cptable=genreporttable3(filelist,labellist); +print(xtable(cptable, caption = "Summary of samples", label = "tab:three", + digits = c(0,0, 0), + align=c('c', 'p{9cm}', 'c'), + table.placement = "tbp", + caption.placement = "top")) +@ + + + + +The meanings of the columns are as follows. + +\begin{itemize} +\item \textbf{Row}: The row number in the table; +\item \textbf{File}: The filename of fastq file; +\item \textbf{Label}: Assigned label; +\item \textbf{Reads}: The total read count in the fastq file; +\item \textbf{Mapped}: Reads that can be mapped to gRNA library; +\item \textbf{Percentage}: The percentage of mapped reads; +\item \textbf{TotalsgRNAs}: The number of sgRNAs in the library; +\item \textbf{ZeroCounts}: The number of sgRNA with 0 read counts; +\item \textbf{GiniIndex}: The Gini Index of the read count distribution. Gini index can be used to measure the evenness of the read counts, and a smaller value means a more even distribution of the read counts. +\end{itemize} + + + +\newpage\section{Normalized read count distribution of all samples} +The following figure shows the distribution of median-normalized read counts in all samples. + + +<<fig=TRUE,echo=FALSE,width=4.5,height=4.5>>= +genboxplot("output.count_normalized.txt"); +@ + +The following figure shows the histogram of median-normalized read counts in all samples. + + +<<fig=TRUE,echo=FALSE,width=4.5,height=4.5>>= +genhistplot("output.count_normalized.txt"); +@ + +%__INDIVIDUAL_PAGE__ + + + +\end{document} + |
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| diff -r 80cf607159ae -r 82a180e6b582 test-data/output_summary.Rnw --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/output_summary.Rnw Wed Apr 04 11:03:05 2018 -0400 |
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| b'@@ -0,0 +1,1063 @@\n+% This is a template file for Sweave used in MAGeCK\n+% Author: Wei Li, Shirley Liu lab\n+% Do not modify lines beginning with "#__".\n+\\documentclass{article}\n+\n+\\usepackage{amsmath}\n+\\usepackage{amscd}\n+\\usepackage[tableposition=top]{caption}\n+\\usepackage{ifthen}\n+\\usepackage{fullpage}\n+\\usepackage[utf8]{inputenc}\n+\n+\\begin{document}\n+\\setkeys{Gin}{width=0.9\\textwidth}\n+\n+\\title{MAGeCK Comparison Report}\n+\\author{Wei Li}\n+\n+\\maketitle\n+\n+\n+\\tableofcontents\n+\n+\\section{Summary}\n+\n+%Function definition\n+<<label=funcdef,include=FALSE,echo=FALSE>>=\n+genreporttable<-function(comparisons,ngenes,direction,fdr1,fdr5,fdr25){\n+ xtb=data.frame(Comparison=comparisons,Genes=ngenes,Selection=direction,FDR1=fdr1,FDR5=fdr5,FDR25=fdr25);\n+ colnames(xtb)=c("Comparison","Genes","Selection","FDR1%","FDR5%","FDR25%");\n+ return (xtb);\n+}\n+@\n+\n+The statistics of comparisons is as indicated in the following table. \n+\n+<<label=tab1,echo=FALSE,results=tex>>=\n+library(xtable)\n+comparisons=c("HL60_final,KBM7_final_vs_HL60_initial,KBM7_initial neg.","HL60_final,KBM7_final_vs_HL60_initial,KBM7_initial pos.");\n+ngenes=c(100,100);\n+direction=c("negative","positive");\n+fdr1=c(0,0);\n+fdr5=c(2,0);\n+fdr25=c(9,1);\n+\n+cptable=genreporttable(comparisons,ngenes,direction,fdr1,fdr5,fdr25);\n+print(xtable(cptable, caption = "Summary of comparisons", label = "tab:one",\n+ digits = c(0, 0, 0, 0, 0, 0, 0),\n+ table.placement = "tbp",\n+ caption.placement = "top"))\n+@\n+\n+The meanings of the columns are as follows.\n+\n+\\begin{itemize}\n+\\item \\textbf{Comparison}: The label for comparisons;\n+\\item \\textbf{Genes}: The number of genes in the library;\n+\\item \\textbf{Selection}: The direction of selection, either positive selection or negative selection;\n+\\item \\textbf{FDR1\\%}: The number of genes with FDR $<$ 1\\%;\n+\\item \\textbf{FDR5\\%}: The number of genes with FDR $<$ 5\\%;\n+\\item \\textbf{FDR25\\%}: The number of genes with FDR $<$ 25\\%;\n+\\end{itemize}\n+\n+The following figures show:\n+\n+\\begin{itemize}\n+\\item Individual sgRNA read counts of selected genes in selected samples; \n+\\item The distribution of RRA scores and p values of all genes; and\n+\\item The RRA scores and p values of selected genes.\n+\\end{itemize}\n+\n+\n+\\newpage\\section{Comparison results of HL60 final,KBM7 final vs HL60 initial,KBM7 initial neg.}\n+\n+The following figure shows the distribution of RRA score in the comparison HL60 final,KBM7 final vs HL60 initial,KBM7 initial neg., and the RRA scores of 10 genes.\n+\n+<<echo=FALSE>>=\n+gstable=read.table(\'output.gene_summary.txt\',header=T)\n+@\n+%\n+\n+\n+<<fig=TRUE,echo=FALSE,width=4.5,height=4.5>>=# \n+#\n+# parameters\n+# Do not modify the variables beginning with "__"\n+\n+# gstablename=\'__GENE_SUMMARY_FILE__\'\n+startindex=3\n+# outputfile=\'__OUTPUT_FILE__\'\n+targetgenelist=c("ACIN1","ACTR8","AHCY","ACLY","AATF","AGBL5","AHCTF1","ABT1","ADIRF","ABCF1")\n+# samplelabel=sub(\'.\\w+.\\w+$\',\'\',colnames(gstable)[startindex]);\n+samplelabel=\'HL60_final,KBM7_final_vs_HL60_initial,KBM7_initial neg.\'\n+\n+\n+# You need to write some codes in front of this code:\n+# gstable=read.table(gstablename,header=T)\n+# pdf(file=outputfile,width=6,height=6)\n+\n+\n+# set up color using RColorBrewer\n+#library(RColorBrewer)\n+#colors <- brewer.pal(length(targetgenelist), "Set1")\n+\n+colors=c( "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#A65628", "#F781BF",\n+ "#999999", "#66C2A5", "#FC8D62", "#8DA0CB", "#E78AC3", "#A6D854", "#FFD92F", "#E5C494", "#B3B3B3", \n+ "#8DD3C7", "#FFFFB3", "#BEBADA", "#FB8072", "#80B1D3", "#FDB462", "#B3DE69", "#FCCDE5",\n+ "#D9D9D9", "#BC80BD", "#CCEBC5", "#FFED6F")\n+\n+######\n+# function definition\n+\n+plotrankedvalues<-function(val, tglist, ...){\n+ \n+ plot(val,log=\'y\',ylim=c(max(val),min(val)),type=\'l\',lwd=2, ...)\n+ if(length(tglist)>0){\n+ for(i in 1:length(tglist)){\n+ targetgene=tglist[i];\n+ tx=which(names(val)==targetgene);ty=val[targetgene];\n+ points(tx,ty,col=colors[(i %% length(colors)) ],cex=2,pch=2'..b'840312603593),c(595.2977492554626,591.3905137762326,1061.787481868224,887.4532212761591),c(1655.0747300287676,943.0281165621008,1069.358159100796,2038.1098479598186),c(626.1650399575977,884.4218494311227,517.3296108924205,858.2719741548927),c(680.5502664327881,747.673892792174,533.1018551269456,1016.194017399393),c(662.9118146029966,777.8650001020718,864.9498738213518,787.3214909580882),c(880.4527205037583,621.5816210861304,671.8976043907657,1040.7978139918332),c(94.07174309222125,447.5387671820139,711.6436598617687,927.5059134033875),c(399.80490814194036,806.280159923152,1147.58849050404,1059.1076161071376),c(698.1887182625796,531.0082991564371,504.0809257354195,347.8862401907832))\n+targetgene="ACSS2"\n+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")\n+\n+# set up color using RColorBrewer\n+#library(RColorBrewer)\n+#colors <- brewer.pal(length(targetgenelist), "Set1")\n+\n+colors=c( "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#A65628", "#F781BF",\n+ "#999999", "#66C2A5", "#FC8D62", "#8DA0CB", "#E78AC3", "#A6D854", "#FFD92F", "#E5C494", "#B3B3B3", \n+ "#8DD3C7", "#FFFFB3", "#BEBADA", "#FB8072", "#80B1D3", "#FDB462", "#B3DE69", "#FCCDE5",\n+ "#D9D9D9", "#BC80BD", "#CCEBC5", "#FFED6F")\n+\n+\n+## code\n+\n+targetmatvec=unlist(targetmat)+1\n+yrange=range(targetmatvec[targetmatvec>0]);\n+# yrange[1]=1; # set the minimum value to 1\n+for(i in 1:length(targetmat)){\n+ vali=targetmat[[i]]+1;\n+ if(i==1){\n+ plot(1:length(vali),vali,type=\'b\',las=1,pch=20,main=paste(\'sgRNAs in\',targetgene),ylab=\'Read counts\',xlab=\'Samples\',xlim=c(0.7,length(vali)+0.3),ylim = yrange,col=colors[(i %% length(colors))],xaxt=\'n\',log=\'y\')\n+ axis(1,at=1:length(vali),labels=(collabel),las=2)\n+ # lines(0:100,rep(1,101),col=\'black\');\n+ }else{\n+ lines(1:length(vali),vali,type=\'b\',pch=20,col=colors[(i %% length(colors))])\n+ }\n+}\n+\n+\n+\n+# parameters\n+# Do not modify the variables beginning with "__"\n+targetmat=list(c(408.62413405683606,523.9045092011671,483.89245311522745,701.494293542599),c(1805.0015705819953,1434.9655709645526,1712.2348341000356,2152.546111180471),c(3017.64513388016,2642.609863360463,1834.6274493599499,3573.2723190648703),c(1649.1952460855039,783.1928425685244,773.4708572611067,1332.0381038883936),c(959.82575373782,1397.6706736993847,1429.5962174173474,2811.126806015325),c(495.34652221997754,301.9110730989776,336.89513684945433,555.015876620164),c(1491.9190506031964,1331.9606166131366,2087.614246881731,1983.1804416139055),c(429.2023278582595,889.7496918975753,567.8007924429005,1132.9190058844583),c(427.7324568724435,573.6310388880576,655.4944703868597,899.4690289143276),c(690.8393633334998,767.2093151691668,1040.33722970927,993.3067647552625))\n+targetgene="ADNP"\n+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")\n+\n+# set up color using RColorBrewer\n+#library(RColorBrewer)\n+#colors <- brewer.pal(length(targetgenelist), "Set1")\n+\n+colors=c( "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#A65628", "#F781BF",\n+ "#999999", "#66C2A5", "#FC8D62", "#8DA0CB", "#E78AC3", "#A6D854", "#FFD92F", "#E5C494", "#B3B3B3", \n+ "#8DD3C7", "#FFFFB3", "#BEBADA", "#FB8072", "#80B1D3", "#FDB462", "#B3DE69", "#FCCDE5",\n+ "#D9D9D9", "#BC80BD", "#CCEBC5", "#FFED6F")\n+\n+\n+## code\n+\n+targetmatvec=unlist(targetmat)+1\n+yrange=range(targetmatvec[targetmatvec>0]);\n+# yrange[1]=1; # set the minimum value to 1\n+for(i in 1:length(targetmat)){\n+ vali=targetmat[[i]]+1;\n+ if(i==1){\n+ plot(1:length(vali),vali,type=\'b\',las=1,pch=20,main=paste(\'sgRNAs in\',targetgene),ylab=\'Read counts\',xlab=\'Samples\',xlim=c(0.7,length(vali)+0.3),ylim = yrange,col=colors[(i %% length(colors))],xaxt=\'n\',log=\'y\')\n+ axis(1,at=1:length(vali),labels=(collabel),las=2)\n+ # lines(0:100,rep(1,101),col=\'black\');\n+ }else{\n+ lines(1:length(vali),vali,type=\'b\',pch=20,col=colors[(i %% length(colors))])\n+ }\n+}\n+\n+\n+\n+par(mfrow=c(1,1));\n+@\n+%__INDIVIDUAL_PAGE__\n+\n+\n+\n+\n+\n+\n+\n+\n+\n+\\end{document}\n+\n' |
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