Mercurial > repos > davidvanzessen > argalaxy_tools
comparison report_clonality/RScript.r @ 10:edbf4fba5fc7 draft
Uploaded
| author | davidvanzessen |
|---|---|
| date | Fri, 31 Jul 2015 08:08:05 -0400 |
| parents | f90fbc15b35a |
| children |
comparison
equal
deleted
inserted
replaced
| 9:079eed22fdb6 | 10:edbf4fba5fc7 |
|---|---|
| 99 } | 99 } |
| 100 | 100 |
| 101 | 101 |
| 102 | 102 |
| 103 #write the complete dataset that is left over, will be the input if 'none' for clonaltype and 'no' for filterproductive | 103 #write the complete dataset that is left over, will be the input if 'none' for clonaltype and 'no' for filterproductive |
| 104 write.table(PRODF, "allUnique.csv", sep=",",quote=F,row.names=F,col.names=T) | 104 write.table(PRODF, "allUnique.txt", sep=",",quote=F,row.names=F,col.names=T) |
| 105 write.table(PRODF, "allUnique.csv", sep="\t",quote=F,row.names=F,col.names=T) | |
| 105 write.table(UNPROD, "allUnproductive.csv", sep=",",quote=F,row.names=F,col.names=T) | 106 write.table(UNPROD, "allUnproductive.csv", sep=",",quote=F,row.names=F,col.names=T) |
| 106 | 107 |
| 107 #write the samples to a file | 108 #write the samples to a file |
| 108 sampleFile <- file("samples.txt") | 109 sampleFile <- file("samples.txt") |
| 109 un = unique(inputdata$Sample) | 110 un = unique(inputdata$Sample) |
| 552 } | 553 } |
| 553 | 554 |
| 554 imgtcolumns = c("X3V.REGION.trimmed.nt.nb","P3V.nt.nb", "N1.REGION.nt.nb", "P5D.nt.nb", "X5D.REGION.trimmed.nt.nb", "X3D.REGION.trimmed.nt.nb", "P3D.nt.nb", "N2.REGION.nt.nb", "P5J.nt.nb", "X5J.REGION.trimmed.nt.nb", "X3V.REGION.trimmed.nt.nb", "X5D.REGION.trimmed.nt.nb", "X3D.REGION.trimmed.nt.nb", "X5J.REGION.trimmed.nt.nb", "N1.REGION.nt.nb", "N2.REGION.nt.nb", "P3V.nt.nb", "P5D.nt.nb", "P3D.nt.nb", "P5J.nt.nb") | 555 imgtcolumns = c("X3V.REGION.trimmed.nt.nb","P3V.nt.nb", "N1.REGION.nt.nb", "P5D.nt.nb", "X5D.REGION.trimmed.nt.nb", "X3D.REGION.trimmed.nt.nb", "P3D.nt.nb", "N2.REGION.nt.nb", "P5J.nt.nb", "X5J.REGION.trimmed.nt.nb", "X3V.REGION.trimmed.nt.nb", "X5D.REGION.trimmed.nt.nb", "X3D.REGION.trimmed.nt.nb", "X5J.REGION.trimmed.nt.nb", "N1.REGION.nt.nb", "N2.REGION.nt.nb", "P3V.nt.nb", "P5D.nt.nb", "P3D.nt.nb", "P5J.nt.nb") |
| 555 if(all(imgtcolumns %in% colnames(inputdata))) | 556 if(all(imgtcolumns %in% colnames(inputdata))) |
| 556 { | 557 { |
| 558 print("MEAN P3V.nt.nb:") | |
| 559 print(PRODF$P3V.nt.nb) | |
| 560 print(mean(PRODF$P3V.nt.nb, na.rm=T)) | |
| 561 print(head(PRODF)) | |
| 557 newData = data.frame(data.table(PRODF)[,list(unique=.N, | 562 newData = data.frame(data.table(PRODF)[,list(unique=.N, |
| 558 VH.DEL=mean(X3V.REGION.trimmed.nt.nb, na.rm=T), | 563 VH.DEL=mean(.SD$X3V.REGION.trimmed.nt.nb, na.rm=T), |
| 559 P1=mean(P3V.nt.nb, na.rm=T), | 564 P1=mean(.SD$P3V.nt.nb, na.rm=T), |
| 560 N1=mean(N1.REGION.nt.nb, na.rm=T), | 565 N1=mean(.SD$N1.REGION.nt.nb, na.rm=T), |
| 561 P2=mean(P5D.nt.nb, na.rm=T), | 566 P2=mean(.SD$P5D.nt.nb, na.rm=T), |
| 562 DEL.DH=mean(X5D.REGION.trimmed.nt.nb, na.rm=T), | 567 DEL.DH=mean(.SD$X5D.REGION.trimmed.nt.nb, na.rm=T), |
| 563 DH.DEL=mean(X3D.REGION.trimmed.nt.nb, na.rm=T), | 568 DH.DEL=mean(.SD$X3D.REGION.trimmed.nt.nb, na.rm=T), |
| 564 P3=mean(P3D.nt.nb, na.rm=T), | 569 P3=mean(.SD$P3D.nt.nb, na.rm=T), |
| 565 N2=mean(N2.REGION.nt.nb, na.rm=T), | 570 N2=mean(.SD$N2.REGION.nt.nb, na.rm=T), |
| 566 P4=mean(P5J.nt.nb, na.rm=T), | 571 P4=mean(.SD$P5J.nt.nb, na.rm=T), |
| 567 DEL.JH=mean(X5J.REGION.trimmed.nt.nb, na.rm=T), | 572 DEL.JH=mean(.SD$X5J.REGION.trimmed.nt.nb, na.rm=T), |
| 568 Total.Del=( mean(X3V.REGION.trimmed.nt.nb, na.rm=T) + | 573 Total.Del=( mean(.SD$X3V.REGION.trimmed.nt.nb, na.rm=T) + |
| 569 mean(X5D.REGION.trimmed.nt.nb, na.rm=T) + | 574 mean(.SD$X5D.REGION.trimmed.nt.nb, na.rm=T) + |
| 570 mean(X3D.REGION.trimmed.nt.nb, na.rm=T) + | 575 mean(.SD$X3D.REGION.trimmed.nt.nb, na.rm=T) + |
| 571 mean(X5J.REGION.trimmed.nt.nb, na.rm=T)), | 576 mean(.SD$X5J.REGION.trimmed.nt.nb, na.rm=T)), |
| 572 | 577 |
| 573 Total.N=( mean(N1.REGION.nt.nb, na.rm=T) + | 578 Total.N=( mean(.SD$N1.REGION.nt.nb, na.rm=T) + |
| 574 mean(N2.REGION.nt.nb, na.rm=T)), | 579 mean(.SD$N2.REGION.nt.nb, na.rm=T)), |
| 575 | 580 |
| 576 Total.P=( mean(P3V.nt.nb, na.rm=T) + | 581 Total.P=( mean(.SD$P3V.nt.nb, na.rm=T) + |
| 577 mean(P5D.nt.nb, na.rm=T) + | 582 mean(.SD$P5D.nt.nb, na.rm=T) + |
| 578 mean(P3D.nt.nb, na.rm=T) + | 583 mean(.SD$P3D.nt.nb, na.rm=T) + |
| 579 mean(P5J.nt.nb, na.rm=T))), | 584 mean(.SD$P5J.nt.nb, na.rm=T))), |
| 580 by=c("Sample")]) | 585 by=c("Sample")]) |
| 581 write.table(newData, "junctionAnalysisProd.csv" , sep=",",quote=F,na="-",row.names=F,col.names=F) | 586 write.table(newData, "junctionAnalysisProd.csv" , sep=",",quote=F,na="-",row.names=F,col.names=F) |
| 582 | 587 |
| 583 newData = data.frame(data.table(UNPROD)[,list(unique=.N, | 588 newData = data.frame(data.table(UNPROD)[,list(unique=.N, |
| 584 VH.DEL=mean(X3V.REGION.trimmed.nt.nb, na.rm=T), | 589 VH.DEL=mean(.SD$X3V.REGION.trimmed.nt.nb, na.rm=T), |
| 585 P1=mean(P3V.nt.nb, na.rm=T), | 590 P1=mean(.SD$P3V.nt.nb, na.rm=T), |
| 586 N1=mean(N1.REGION.nt.nb, na.rm=T), | 591 N1=mean(.SD$N1.REGION.nt.nb, na.rm=T), |
| 587 P2=mean(P5D.nt.nb, na.rm=T), | 592 P2=mean(.SD$P5D.nt.nb, na.rm=T), |
| 588 DEL.DH=mean(X5D.REGION.trimmed.nt.nb, na.rm=T), | 593 DEL.DH=mean(.SD$X5D.REGION.trimmed.nt.nb, na.rm=T), |
| 589 DH.DEL=mean(X3D.REGION.trimmed.nt.nb, na.rm=T), | 594 DH.DEL=mean(.SD$X3D.REGION.trimmed.nt.nb, na.rm=T), |
| 590 P3=mean(P3D.nt.nb, na.rm=T), | 595 P3=mean(.SD$P3D.nt.nb, na.rm=T), |
| 591 N2=mean(N2.REGION.nt.nb, na.rm=T), | 596 N2=mean(.SD$N2.REGION.nt.nb, na.rm=T), |
| 592 P4=mean(P5J.nt.nb, na.rm=T), | 597 P4=mean(.SD$P5J.nt.nb, na.rm=T), |
| 593 DEL.JH=mean(X5J.REGION.trimmed.nt.nb, na.rm=T), | 598 DEL.JH=mean(.SD$X5J.REGION.trimmed.nt.nb, na.rm=T), |
| 594 Total.Del=( mean(X3V.REGION.trimmed.nt.nb, na.rm=T) + | 599 Total.Del=( mean(.SD$X3V.REGION.trimmed.nt.nb, na.rm=T) + |
| 595 mean(X5D.REGION.trimmed.nt.nb, na.rm=T) + | 600 mean(.SD$X5D.REGION.trimmed.nt.nb, na.rm=T) + |
| 596 mean(X3D.REGION.trimmed.nt.nb, na.rm=T) + | 601 mean(.SD$X3D.REGION.trimmed.nt.nb, na.rm=T) + |
| 597 mean(X5J.REGION.trimmed.nt.nb, na.rm=T)), | 602 mean(.SD$X5J.REGION.trimmed.nt.nb, na.rm=T)), |
| 598 | 603 |
| 599 Total.N=( mean(N1.REGION.nt.nb, na.rm=T) + | 604 Total.N=( mean(.SD$N1.REGION.nt.nb, na.rm=T) + |
| 600 mean(N2.REGION.nt.nb, na.rm=T)), | 605 mean(.SD$N2.REGION.nt.nb, na.rm=T)), |
| 601 | 606 |
| 602 Total.P=( mean(P3V.nt.nb, na.rm=T) + | 607 Total.P=( mean(.SD$P3V.nt.nb, na.rm=T) + |
| 603 mean(P5D.nt.nb, na.rm=T) + | 608 mean(.SD$P5D.nt.nb, na.rm=T) + |
| 604 mean(P3D.nt.nb, na.rm=T) + | 609 mean(.SD$P3D.nt.nb, na.rm=T) + |
| 605 mean(P5J.nt.nb, na.rm=T))), | 610 mean(.SD$P5J.nt.nb, na.rm=T))), |
| 606 by=c("Sample")]) | 611 by=c("Sample")]) |
| 607 write.table(newData, "junctionAnalysisUnProd.csv" , sep=",",quote=F,na="-",row.names=F,col.names=F) | 612 write.table(newData, "junctionAnalysisUnProd.csv" , sep=",",quote=F,na="-",row.names=F,col.names=F) |
| 608 } | 613 } |
| 609 | 614 |
| 610 # ---------------------- AA composition in CDR3 ---------------------- | 615 # ---------------------- AA composition in CDR3 ---------------------- |