script: /data/user2/work/80/statistics~DESeq2 "$scriptdir"/statistics~scatter_with_variance
c2997108/centos6:3 c2997108/centos7:1-trinity_2.8.5-kallisto_0.46.0 c2997108/centos7:1-trinity_2.8.5-kallisto_0.46.0-blast_2.9.0-trinotate-3.1.1-R_3-kegg_2 c2997108/centos7:1-trinity_2.8.5-kallisto_0.46.0-blast_2.9.0-trinotate-3.1.1-R_4-kegg_4 centos:centos6
using docker
+ set -o pipefail
+ script=run-DESeq2.0h_B_1.fq.gz.1week_A1_1.fq.gz.gene.R
+ inputsamplematrix=sample.input.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt
+ inputmatrix=kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt
+ g1=0h_B_1.fq.gz
+ g2=1week_A1_1.fq.gz
+ '[' 0h_B_1.fq.gz = '' ']'
+ '[' 1week_A1_1.fq.gz = '' ']'
+ p=0.05
++ basename kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt
+ outputfile=DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt
++ basename sample.input.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt
++ basename kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt
+ samplex=DESeq2.sample.input.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.x
++ basename sample.input.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt
++ basename kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt
+ sampley=DESeq2.sample.input.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.y
++ basename kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt
+ outputfilexup=result.DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.0h_B_1.fq.gz.up.1week_A1_1.fq.gz.down.txt
++ basename kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt
+ outputfileyup=result.DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.0h_B_1.fq.gz.down.1week_A1_1.fq.gz.up.txt
+ '[' Trinotate.xls3.gene.cnt = '' ']'
+ annotationfile=Trinotate.xls3.gene.cnt
+ cat
+ docker run -v /data/user2/work/80:/data/user2/work/80 -w /data/user2/work/80 -u root -i --rm c2997108/centos7:1-trinity_2.8.5-kallisto_0.46.0-blast_2.9.0-trinotate-3.1.1-R_4-kegg_4 R --vanilla

R version 3.5.2 (2018-12-20) -- "Eggshell Igloo"
Copyright (C) 2018 The R Foundation for Statistical Computing
Platform: x86_64-redhat-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(DESeq2)
Loading required package: S4Vectors
Loading required package: stats4
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, sd, var, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, basename, cbind, colMeans, colSums, colnames,
    dirname, do.call, duplicated, eval, evalq, get, grep, grepl,
    intersect, is.unsorted, lapply, lengths, mapply, match, mget,
    order, paste, pmax, pmax.int, pmin, pmin.int, rank, rbind,
    rowMeans, rowSums, rownames, sapply, setdiff, sort, table, tapply,
    union, unique, unsplit, which, which.max, which.min


Attaching package: 'S4Vectors'

The following object is masked from 'package:base':

    expand.grid

Loading required package: IRanges
Loading required package: GenomicRanges
Loading required package: GenomeInfoDb
Loading required package: SummarizedExperiment
Loading required package: Biobase
Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

Loading required package: DelayedArray
Loading required package: matrixStats

Attaching package: 'matrixStats'

The following objects are masked from 'package:Biobase':

    anyMissing, rowMedians

Loading required package: BiocParallel

Attaching package: 'DelayedArray'

The following objects are masked from 'package:matrixStats':

    colMaxs, colMins, colRanges, rowMaxs, rowMins, rowRanges

The following objects are masked from 'package:base':

    aperm, apply

> colData <- read.table("sample.input.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt", header=T, row.names=1, sep="\t")
> countData=round(read.table("kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt",sep="\t",header=T,row.names=1))
> mydata=data.frame("group"=as.character(colData[,1]),stringsAsFactors=F)
> dds <- DESeqDataSetFromMatrix(countData = countData, colData = mydata, design = ~ group)
converting counts to integer mode
Warning message:
In DESeqDataSet(se, design = design, ignoreRank) :
  some variables in design formula are characters, converting to factors
> dds <- DESeq(dds)
estimating size factors
estimating dispersions
Error in checkForExperimentalReplicates(object, modelMatrix) : 

  The design matrix has the same number of samples and coefficients to fit,
  so estimation of dispersion is not possible. Treating samples
  as replicates was deprecated in v1.20 and no longer supported since v1.22.

Calls: DESeq ... estimateDispersions -> .local -> checkForExperimentalReplicates
Execution halted
+ true
+ '[' '!' -e DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt ']'
+ touch DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt
+ tail -n+2 DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt
+ cut -f 1
+ awk '-F\t' -v g1=0h_B_1.fq.gz '$2==g1{print $1}' sample.input.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt
+ awk '-F\t' -v g2=1week_A1_1.fq.gz '$2==g2{print $1}' sample.input.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt
+ bash /data/user2/work/80/statistics~scatter_with_variance -x 0h_B_1.fq.gz -y 1week_A1_1.fq.gz kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.id DESeq2.sample.input.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.x DESeq2.sample.input.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.y
c2997108/centos6:3 c2997108/centos7:1-trinity_2.8.5-kallisto_0.46.0 c2997108/centos7:1-trinity_2.8.5-kallisto_0.46.0-blast_2.9.0-trinotate-3.1.1-R_3-kegg_2 c2997108/centos7:1-trinity_2.8.5-kallisto_0.46.0-blast_2.9.0-trinotate-3.1.1-R_4-kegg_4 centos:centos6
using docker
+ set -o pipefail
+ countmat=kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt
+ sigmat=DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.id
+ listx=DESeq2.sample.input.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.x
+ listy=DESeq2.sample.input.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.y
+ label_x=0h_B_1.fq.gz
+ label_y=1week_A1_1.fq.gz
+ p=0.05
++ basename kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt
++ basename DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.id
+ output=kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.id
+ cat kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt
+ awk '-F\t' 'FILENAME==ARGV[1]{if(FNR>1){for(i=2;i<=NF;i++){a[i]+=$i}}} FILENAME==ARGV[2]{if(FNR==1){print $0}else{ORS=""; print $1;for(i=2;i<=NF;i++){print "\t"$i/a[i]*1000*1000}; print "\n"}}' /dev/stdin kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt
+ cat DESeq2.sample.input.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.x
+ awk '-F\t' 'FILENAME==ARGV[1]{a[$1]=1} FILENAME==ARGV[2]{if(FNR==1){for(i=1;i<=NF;i++){if(a[$i]==1){b[i]=1}}}; ORS=""; print $1; for(i=2;i<=NF;i++){if(b[i]==1){print "\t"$i}}; print "\n"}' /dev/stdin kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.id.cpm
+ cat DESeq2.sample.input.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.y
+ awk '-F\t' 'FILENAME==ARGV[1]{a[$1]=1} FILENAME==ARGV[2]{if(FNR==1){for(i=1;i<=NF;i++){if(a[$i]==1){b[i]=1}}}; ORS=""; print $1; for(i=2;i<=NF;i++){if(b[i]==1){print "\t"$i}}; print "\n"}' /dev/stdin kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.id.cpm
+ cat DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.id
+ awk '-F\t' 'FILENAME==ARGV[1]{a[$1]=1} FILENAME==ARGV[2] && (FNR==1 || a[$1]==1){print $0}' /dev/stdin kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.id.cpm_x
+ cat DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.id
+ awk '-F\t' 'FILENAME==ARGV[1]{a[$1]=1} FILENAME==ARGV[2] && (FNR==1 || a[$1]==1){print $0}' /dev/stdin kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.id.cpm_y
+ cat
+ docker run -v /data/user2/work/80:/data/user2/work/80 -w /data/user2/work/80 -u root -i --rm c2997108/centos7:1-trinity_2.8.5-kallisto_0.46.0-blast_2.9.0-trinotate-3.1.1-R_4-kegg_4 R --vanilla

R version 3.5.2 (2018-12-20) -- "Eggshell Igloo"
Copyright (C) 2018 The R Foundation for Statistical Computing
Platform: x86_64-redhat-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> 
> label_x="0h_B_1.fq.gz"
> label_y="1week_A1_1.fq.gz"
> file_data_x="kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.id.cpm_x"
> file_data_y="kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.id.cpm_y"
> file_sig_data_x="kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.id.cpm_x_sig"
> file_sig_data_y="kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.id.cpm_y_sig"
> data_x=round(read.table(file_data_x,sep="\t",header=T,row.names=1))
> data_y=round(read.table(file_data_y,sep="\t",header=T,row.names=1))
> sig_data_x=read.table(file_sig_data_x,sep="\t",header=T,row.names=1)
> if(dim(sig_data_x)[1]!=0){sig_data_x=round(sig_data_x)}
> sig_data_y=read.table(file_sig_data_y,sep="\t",header=T,row.names=1)
> if(dim(sig_data_y)[1]!=0){sig_data_y=round(sig_data_y)}
> mean_data_x=apply(data_x,1,mean)
> mean_data_y=apply(data_y,1,mean)
> if(dim(data_x)[2]>1){
+  dx=apply(data_x,1,function(i){return(abs(qt(0.05/2, length(i)-1)) * sd(i) / sqrt(length(i)))})
+ }else{
+  dx=0
+ }
> if(dim(data_y)[2]>1){
+  dy=apply(data_y,1,function(i){return(abs(qt(0.05/2, length(i)-1)) * sd(i) / sqrt(length(i)))})
+ }else{
+  dy=0
+ }
> vx=dx/mean_data_x
> vy=dy/mean_data_y
> vx[is.na(vx)]=0
> vy[is.na(vy)]=0
> #total_var_data=sqrt(dx^2+dy^2)/sqrt(mean_data_x^2+mean_data_y^2)
> #total_var_data[is.na(total_var_data)]=0
> total_var_data=sqrt(vx^2+vy^2)
> mean_sig_data_x=apply(sig_data_x,1,mean)
> mean_sig_data_y=apply(sig_data_y,1,mean)
> min_x=min(mean_data_x[mean_data_x>0])/10
> min_y=min(mean_data_y[mean_data_y>0])/10
> plot_mean_data_x=mean_data_x+min_x
> plot_mean_data_y=mean_data_y+min_y
> plot_mean_sig_data_x=mean_sig_data_x+min_x
> plot_mean_sig_data_y=mean_sig_data_y+min_y
> max_x=max(plot_mean_data_x)
> max_y=max(plot_mean_data_y)
> library(Cairo)
> mainplotfunc=function(){
+ if(max(dx,dy)>0){
+  start_class=quantile(total_var_data[total_var_data>0],c(0,1,25,50,75,90,100)/100)[2]
+  end_class=quantile(total_var_data[total_var_data>0],c(0,1,25,50,75,90,100)/100)[6]
+ 
+  CairoPNG("kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.id.scatter.png",width=800,height=600)
+  num_class=22
+  library(RColorBrewer)
+  #mycol=colorRampPalette(c(rgb(0.5,0,0.2,0.4),rgb(1,0.8,0.7,1)), alpha=TRUE)(num_class)
+  colPal3 <- colorRampPalette(brewer.pal(9,"YlOrRd")[3:9])
+  mycol=colPal3(num_class)
+ 
+  layout(matrix(c(1,1,1,1,2),1,5))
+  par(ps = 18)
+  k=0
+  i=end_class
+  n=(total_var_data>=i)
+  xt=plot_mean_data_x[n]
+  yt=plot_mean_data_y[n]
+  plot(xt,yt,log="xy",xlim=c(min_x,max_x),ylim=c(min_y,max_y),cex=2*(k+1)^3/num_class^3,pch=21,col=adjustcolor(mycol[k+1],0),bg=adjustcolor(mycol[k+1],1-0.4*k/num_class),xlab=label_x,ylab=label_y)
+ 
+  for(k in 1:(num_class-2)){
+   i=end_class+(start_class-end_class)*k/(num_class-2)
+   n=(total_var_data>=i & total_var_data<i+(end_class-start_class)/(num_class-2))
+   xt=plot_mean_data_x[n]
+   yt=plot_mean_data_y[n]
+   par(new=T)
+   plot(xt,yt,log="xy",xlim=c(min_x,max_x),ylim=c(min_y,max_y),cex=2*(k+1)^3/num_class^3,pch=21,col=adjustcolor(mycol[k+1],0),bg=adjustcolor(mycol[k+1],1-0.4*k/num_class),axes=F,xlab="",ylab="")
+  }
+  k=num_class-1
+  i=min(total_var_data)
+  n=(total_var_data>=i & total_var_data<start_class)
+  xt=plot_mean_data_x[n]
+  yt=plot_mean_data_y[n]
+  par(new=T)
+  plot(xt,yt,log="xy",xlim=c(min_x,max_x),ylim=c(min_y,max_y),cex=2*(k+1)^3/num_class^3,pch=21,col=adjustcolor(mycol[k+1],0),bg=adjustcolor(mycol[k+1],1-0.4*k/num_class),axes=F,xlab="",ylab="")
+ 
+  par(new=T)
+  plot(plot_mean_sig_data_x,plot_mean_sig_data_y,log="xy",xlim=c(min_x,max_x),ylim=c(min_y,max_y),col="green",cex=2,axes=F,xlab="",ylab="")
+ 
+  plot(c(0,0),c(-1,num_class),xlim=c(0,0),ylim=c(-1,num_class),cex=0,bty="n",axes=F,xlab="",ylab="")
+  for(k in 0:(num_class-2)){
+   i=end_class+(start_class-end_class)*k/(num_class-2)
+   par(new=T)
+   plot(c(0),c(k),xlim=c(0,0),ylim=c(-1,num_class),col=adjustcolor(mycol[k+1],0),bg=adjustcolor(mycol[k+1],1-0.4*k/num_class),pch=21,cex=2*(k+1)^3/num_class^3,bty="n",axes=F,xlab="",ylab="")
+   text(c(0.05),c(k),paste(">=",i),pos=4)
+  }
+  k=num_class-1
+  i=min(total_var_data)
+  par(new=T)
+  plot(c(0),c(k),xlim=c(0,0),ylim=c(-1,num_class),col=adjustcolor(mycol[k+1],0),bg=adjustcolor(mycol[k+1],1-0.4*k/num_class),pch=21,cex=2*(k+1)^3/num_class^3,bty="n",axes=F,xlab="",ylab="")
+  text(c(0.05),c(k),paste(">=",i),pos=4)
+  text(0,num_class+0.2,"95%conf/mean")
+  par(new=T)
+  plot(c(-0.3),c(-1),xlim=c(0,0),ylim=c(-1,num_class),col="green",cex=1,bty="n",axes=F,xlab="",ylab="")
+  text(c(-0.3),c(-1),paste("significant"),pos=4)
+ 
+  dev.off()
+ }
+ }
> subplotfunc=function(){
+ CairoPNG("kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.id.scatter.normal.png",width=600,height=600)
+ plot(plot_mean_data_x,plot_mean_data_y,log="xy",xlim=c(min_x,max_x),ylim=c(min_y,max_y),cex=0.1,pch=21,col=adjustcolor("#000000",0.5),xlab=label_x,ylab=label_y)
+ par(new=T)
+ plot(plot_mean_sig_data_x,plot_mean_sig_data_y,log="xy",xlim=c(min_x,max_x),ylim=c(min_y,max_y),col="green",cex=2,axes=F,xlab="",ylab="")
+ dev.off()
+ }
> 
> wflag=0
> while(wflag<=5){
+  restry=NULL
+  restry=try(mainplotfunc(), silent = FALSE)
+  if(class(restry)!="try-error"){break}
+  try(dev.off())
+  Sys.sleep(10+runif(1, min=0,max=100)/10)
+  wflag=wflag+1
+ }
> wflag=0
> while(wflag<=5){
+  restry=NULL
+  restry=try(subplotfunc(), silent = FALSE)
+  if(class(restry)!="try-error"){break}
+  try(dev.off())
+  Sys.sleep(10+runif(1, min=0,max=100)/10)
+  wflag=wflag+1
+ }
> 
> 
> 
+ rm -f kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.id.cpm kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.id.cpm_x kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.id.cpm_y kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.id.cpm_x_sig kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.id.cpm_y_sig
+ post_processing
+ '[' 3 = 1 ']'
+ exit
+ awk '{if($3>=0){print $1"\tx"}else{print $1"\ty"}}'
+ tail -n+2 DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt
+ awk '-F\t' 'NR==1{print "id\t"$0} NR>1{print $0}' DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt
+ cut -f 1,7
+ awk '-F\t' 'NR==1{print -1"\t"$0} NR>1{print $2"\t"$0}'
+ sort -k1,1g
+ cut -f 2-
+ awk '-F\t' 'FILENAME==ARGV[1]{xy[$1]=$2} FILENAME==ARGV[2]{if(FNR==1){header=$0}; res[$1]=$0} FILENAME==ARGV[3]{if(FNR==1){print header"\t"$2}else{if(xy[$1]=="x"){print res[$1]"\t"$2}}}' DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.xy Trinotate.xls3.gene.cnt DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.p
+ awk '-F\t' 'FILENAME==ARGV[1]{xy[$1]=$2} FILENAME==ARGV[2]{if(FNR==1){header=$0}; res[$1]=$0} FILENAME==ARGV[3]{if(FNR==1){print header"\t"$2}else{if(xy[$1]=="y"){print res[$1]"\t"$2}}}' DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.xy Trinotate.xls3.gene.cnt DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.p
+ i=result.DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.0h_B_1.fq.gz.up.1week_A1_1.fq.gz.down.txt
+ sed 's/\t$//'
+ awk '-F\t' -v maxlen=30000 'FILENAME==ARGV[1]{for(i=1;i<=NF;i++){n=int((length($i)-1)/maxlen)+1; if(n>a[i]){a[i]=n}}} FILENAME==ARGV[2]{if(FNR==1){ORS=""; for(i=1;i<=NF;i++){if(a[i]<=1){print $i"\t"}else{for(j=1;j<=a[i];j++){print $i" (split "j")\t"}}}; print "\n"}else{for(i=1;i<=NF;i++){if(a[i]<=1){print $i"\t"}else{for(j=1;j<=a[i];j++){print substr($i,(j-1)*maxlen+1,maxlen)"\t" }}}; print "\n"}}' result.DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.0h_B_1.fq.gz.up.1week_A1_1.fq.gz.down.txt ./result.DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.0h_B_1.fq.gz.up.1week_A1_1.fq.gz.down.txt
+ i=result.DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.0h_B_1.fq.gz.down.1week_A1_1.fq.gz.up.txt
+ awk '-F\t' -v maxlen=30000 'FILENAME==ARGV[1]{for(i=1;i<=NF;i++){n=int((length($i)-1)/maxlen)+1; if(n>a[i]){a[i]=n}}} FILENAME==ARGV[2]{if(FNR==1){ORS=""; for(i=1;i<=NF;i++){if(a[i]<=1){print $i"\t"}else{for(j=1;j<=a[i];j++){print $i" (split "j")\t"}}}; print "\n"}else{for(i=1;i<=NF;i++){if(a[i]<=1){print $i"\t"}else{for(j=1;j<=a[i];j++){print substr($i,(j-1)*maxlen+1,maxlen)"\t" }}}; print "\n"}}' result.DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.0h_B_1.fq.gz.down.1week_A1_1.fq.gz.up.txt ./result.DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.0h_B_1.fq.gz.down.1week_A1_1.fq.gz.up.txt
+ sed 's/\t$//'
+ docker run -v /data/user2/work/80:/data/user2/work/80 -w /data/user2/work/80 -u root -i --rm c2997108/centos7:1-trinity_2.8.5-kallisto_0.46.0-blast_2.9.0-trinotate-3.1.1-R_4-kegg_4 java -Xmx1G -jar /usr/local/bin/excel2.jar result.DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.0h_B_1.fq.gz.up.1week_A1_1.fq.gz.down.txt.temp result.DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.0h_B_1.fq.gz.up.1week_A1_1.fq.gz.down.txt.xlsx
Start converting
+ docker run -v /data/user2/work/80:/data/user2/work/80 -w /data/user2/work/80 -u root -i --rm c2997108/centos7:1-trinity_2.8.5-kallisto_0.46.0-blast_2.9.0-trinotate-3.1.1-R_4-kegg_4 java -Xmx1G -jar /usr/local/bin/excel2.jar result.DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.0h_B_1.fq.gz.down.1week_A1_1.fq.gz.up.txt.temp result.DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.0h_B_1.fq.gz.down.1week_A1_1.fq.gz.up.txt.xlsx
Start converting
+ rm -f DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.id DESeq2.sample.input.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.x DESeq2.sample.input.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.y DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.xy DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.p result.DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.0h_B_1.fq.gz.up.1week_A1_1.fq.gz.down.txt.temp result.DESeq2.kallisto.gene.counts.matrix.0h_B_1.fq.gz.1week_A1_1.fq.gz.txt.0h_B_1.fq.gz.down.1week_A1_1.fq.gz.up.txt.temp
+ post_processing
+ '[' 2 = 1 ']'
+ exit