UnboundLocalError: local variable 'seqHead' referenced before assignment

[linqy-immune]

Hi, @s175573
I'm here again.
Thank you for your wonderful work!
Recently I try to analyze my data by GIANA, but when I run python GIANA4.1.py -f my_data.tsv, something goes wrong as the error appears UnboundLocalError: local variable 'seqHead' referenced before assignment.(even this error happens when I run the tutorial file)
Could you please give me some advice?
Looking forward to your reply.
Thanks and best regards,
Linqy

[s175573]

What is your python version please?

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________________________________ From: linqy-immune ***@***.***> Sent: Friday, June 20, 2025 11:31 AM To: s175573/GIANA ***@***.***> Cc: Li, Bo ***@***.***>; Mention ***@***.***> Subject: [External][s175573/GIANA] UnboundLocalError: local variable 'seqHead' referenced before assignment (Issue #21) [https://avatars.githubusercontent.com/u/188452455?s=20&v=4]linqy-immune created an issue (s175573/GIANA#21)<#21> Hi, @s175573<https://github.com/s175573> I'm here again. Thank you for your wonderful work! Recently I try to analyze my data by GIANA, but when I run python GIANA4.1.py -f my_data.tsv, something goes wrong as the error appears UnboundLocalError: local variable 'seqHead' referenced before assignment. Could you please give me some advice? Looking forward to your reply. Thanks and best regards, Linqy — Reply to this email directly, view it on GitHub<#21>, or unsubscribe<https://github.com/notifications/unsubscribe-auth/AKWYQCYMHGBJKWCW6POVBTL3EQSMNAVCNFSM6AAAAAB7YTKLCWVHI2DSMVQWIX3LMV43ASLTON2WKOZTGE3DGNZRGEYTIMI>. You are receiving this because you were mentioned.Message ID: ***@***.***> ** This email originated from an EXTERNAL sender to CHOP. Proceed with caution when replying, opening attachments, or clicking links. Do not disclose your CHOP credentials, employee information, or protected health information to a potential hacker**.

[linqy-immune]

Hi, @s175573
It is Python 3.10.16 | packaged by conda-forge | (main, Dec 5 2024, 14:16:10) [GCC 13.3.0] on linux.
I find that the requirement for GIANA is GIANA is written in Python3, with the following dependencies, should I do some changes?

[linqy-immune]

Hello!
I'm sorry to bother you again cause there is another question. I am a little confused about how I can convert my data from the adaptive format into imgt format by ProcessAdaptiveFile.R? I have tried PrepareAdaptiveFile(indir,outdir,thr=10000) but it doesn't work.

[s175573]

Can you paste the error message? Thanks, Bo

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________________________________ From: linqy-immune ***@***.***> Sent: Saturday, June 21, 2025 11:45 AM To: s175573/GIANA ***@***.***> Cc: Li, Bo ***@***.***>; Mention ***@***.***> Subject: [External]Re: [s175573/GIANA] UnboundLocalError: local variable 'seqHead' referenced before assignment (Issue #21) [https://avatars.githubusercontent.com/u/188452455?s=20&v=4]linqy-immune left a comment (s175573/GIANA#21)<#21 (comment)> Hello! I'm sorry to bother you again cause there is another question. I am a little confused about how I can convert my data from the adaptive format into imgt format by ProcessAdaptiveFile.R? I have tried PrepareAdaptiveFile(indir,outdir,thr=10000) but it doesn't work. — Reply to this email directly, view it on GitHub<#21 (comment)>, or unsubscribe<https://github.com/notifications/unsubscribe-auth/AKWYQC3NGSNO2LVWP6YOILL3EV4YNAVCNFSM6AAAAAB7YTKLCWVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDSOJTGY2DEOJSGE>. You are receiving this because you were mentioned.Message ID: ***@***.***> ** This email originated from an EXTERNAL sender to CHOP. Proceed with caution when replying, opening attachments, or clicking links. Do not disclose your CHOP credentials, employee information, or protected health information to a potential hacker**.

[linqy-immune]

Hello,
Let me show how I run:

1. indir = '/home/TCR/adaptive_imgt'
2. outdir = '/home/TCR/adaptive_imgt/new'
3. ProcessAdaptiveVgenes <- function(dd){

• Vgene_o=c(1,2,9,13:19,26:28,30)
• Vgene_o=as.character(Vgene_o)
• dd=dd[which(nchar(as.character(dd[,2]))>0),]
• gsub('TCRBV[0]{0,1}','TRBV',dd[,2])->tmpV
• vv.m=grep('/',tmpV)
• if(length(vv.m)>0){

• TMP=strsplit(tmpV[vv.m],'/')
  

• tmpV[vv.m]=unlist(sapply(TMP,function(x)x[1]))
  

• }
• vv.m=grep(',',tmpV)
• if(length(vv.m)>0){

• TMP=strsplit(tmpV[vv.m],',')
  

• tmpV[vv.m]=unlist(sapply(TMP,function(x)x[1]))
  

• }
• tmpV=gsub('-0','-',tmpV)
• v_digit=grep('\*',tmpV)
• if(length(v_digit)>0)tmpV[- v_digit] = paste(tmpV[- v_digit],'*01',sep='') else tmpV=paste(tmpV,'*01',sep='')
• Vnumbers=gsub('TRBV','',tmpV)
• Vnumbers=gsub('\*.+','',Vnumbers)
• Vnumbers=gsub('-.+','',Vnumbers)
• vv.o=which(Vnumbers %in% Vgene_o)
• tmpV1=tmpV
• tmpV1[vv.o]=gsub('-1','',tmpV1[vv.o])
• vv.no=which(! Vnumbers %in% Vgene_o)
• vv.non=grep('-',tmpV1[vv.no])
• if(length(vv.non)>0)tmpV1[vv.no][-vv.non]=gsub('\01','-101',tmpV1[vv.no][-vv.non])
• dd[,2]=tmpV1
• return(dd)
• }

4. PrepareAdaptiveFile <- function(indir,outdir,thr=10000){

• ffs=dir(indir,full.names=T)
• for(ff in ffs){

• if(length(grep('\\.tsv|\\.txt',ff))==0 ) next
  

• ff0=unlist(strsplit(ff,'\\/'))
  

• ff0=ff0[length(ff0)]
  

• if(!file.exists(outdir))dir.create(outdir)
  

• newff=paste(outdir,'TestReal-',ff0,sep='')
  

• if(exists(newff))next
  

• print(ff)
  

• ddnew=read.table(ff,header=T,sep='\t',stringsAsFactors=F)
  

• tmp.vv.rm=grep('\\*',ddnew[,2])
  

• if(length(tmp.vv.rm)>0)ddnew=ddnew[-tmp.vv.rm,]
  

• tmp.vv.rm=grep('X',ddnew[,2])
  

• if(length(tmp.vv.rm)>0)ddnew=ddnew[-tmp.vv.rm,]
  

• tmp.nn=nchar(ddnew[,2])
  

• tmp.vv=which(tmp.nn>=10 & tmp.nn<=24)
  

• #tmp.vv=which(tmp.nn>=1)
  

• ddnew=ddnew[tmp.vv,]
  

• ddnew=ddnew[which(ddnew[,6]!='unresolved'),]
  

• ddnew=ddnew[grep('^C.+[FV]$',ddnew[,2]),]
  

• #ss=sum(ddnew[,3])
  

• #ddnew[,4]=ddnew[,3]/ss
  

• ddnew=ddnew[order(ddnew[,4],decreasing=T),]
  

• #q75=quantile(ddnew[,3],0.75)
  

• #THR=min(ddnew[,3]+1)
  

• #tmp.vv=which(ddnew[,3]>max(q75,THR))
  

• #if(length(tmp.vv)<=thr)tmp.vv=1:thr
  

• if(nrow(ddnew)>thr)ddnew=ddnew[1:thr,c(2,6,4)] else ddnew=ddnew[,c(2,6,4)]
  

• #ddnew=ddnew[1:5000,]
  

• ddnew=ddnew[1:min(thr,nrow(ddnew)),]
  

• ddnew=ProcessAdaptiveVgenes(ddnew)
  

• ddnew=cbind(ddnew, RANK=rank(ddnew[,3])/nrow(ddnew))
  

• TMP=gsub('.+/TCR_peptide/data/Adaptive/','',indir)
  

• tmp=strsplit(TMP,'/')[[1]][[1]]
  

• ddnew=cbind(ddnew, Info=paste(tmp,ff0,sep=':'))
  

• write.table(ddnew,file=newff,quote=F,sep='\t',row.names=F)
  

• }
• }

5. PrepareAdaptiveFile(indir,outdir,thr=10000)

The data I run is downloaded from adaptiveBiotechnology. The error was:Error in [<-.data.frame(*tmp*, , 2, value = "*01") : replacement has 1 row, data has 0.
Waht should I need to adjust now?
Thanks and best regards,
Linqy

[s175573]

Can you check your data to make sure that enough TCRs passed filter? It seems that there isn't anything with a standard V gene left.

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________________________________ From: linqy-immune ***@***.***> Sent: Saturday, June 21, 2025 9:20 PM To: s175573/GIANA ***@***.***> Cc: Li, Bo ***@***.***>; Mention ***@***.***> Subject: [External]Re: [s175573/GIANA] UnboundLocalError: local variable 'seqHead' referenced before assignment (Issue #21) [https://avatars.githubusercontent.com/u/188452455?s=20&v=4]linqy-immune left a comment (s175573/GIANA#21)<#21 (comment)> Hello, Let me show how I run: 1. indir = '/home/TCR/adaptive_imgt' 2. outdir = '/home/TCR/adaptive_imgt/new' 3. ProcessAdaptiveVgenes <- function(dd){ * Vgene_o=c(1,2,9,13:19,26:28,30) * Vgene_o=as.character(Vgene_o) * dd=dd[which(nchar(as.character(dd[,2]))>0),] * gsub('TCRBV[0]{0,1}','TRBV',dd[,2])->tmpV * Multiple calls * vv.m=grep('/',tmpV) * if(length(vv.m)>0){ * TMP=strsplit(tmpV[vv.m],'/') * tmpV[vv.m]=unlist(sapply(TMP,function(x)x[1])) * } * vv.m=grep(',',tmpV) * if(length(vv.m)>0){ * TMP=strsplit(tmpV[vv.m],',') * tmpV[vv.m]=unlist(sapply(TMP,function(x)x[1])) * } * tmpV=gsub('-0','-',tmpV) * v_digit=grep('\*',tmpV) * if(length(v_digit)>0)tmpV[- v_digit] = paste(tmpV[- v_digit],'*01',sep='') else tmpV=paste(tmpV,'*01',sep='') * 1. Orphan V genes do not have "-1", need to remove * Vnumbers=gsub('TRBV','',tmpV) * Vnumbers=gsub('\*.+','',Vnumbers) * Vnumbers=gsub('-.+','',Vnumbers) * vv.o=which(Vnumbers %in% Vgene_o) * tmpV1=tmpV * tmpV1[vv.o]=gsub('-1','',tmpV1[vv.o]) * 2. Non-orphan V genes but without "-1", need to add * vv.no=which(! Vnumbers %in% Vgene_o) * vv.non=grep('-',tmpV1[vv.no]) * if(length(vv.non)>0)tmpV1[vv.no][-vv.non]=gsub('\01','-101',tmpV1[vv.no][-vv.non]) * dd[,2]=tmpV1 * return(dd) * } 1. PrepareAdaptiveFile <- function(indir,outdir,thr=10000){ * ffs=dir(indir,full.names=T) * for(ff in ffs){ * if(length(grep('\\.tsv|\\.txt',ff))==0 ) next * ff0=unlist(strsplit(ff,'\\/')) * ff0=ff0[length(ff0)] * if(!file.exists(outdir))dir.create(outdir) * newff=paste(outdir,'TestReal-',ff0,sep='') * if(exists(newff))next * print(ff) * ddnew=read.table(ff,header=T,sep='\t',stringsAsFactors=F) * tmp.vv.rm=grep('\\*',ddnew[,2]) * if(length(tmp.vv.rm)>0)ddnew=ddnew[-tmp.vv.rm,] * tmp.vv.rm=grep('X',ddnew[,2]) * if(length(tmp.vv.rm)>0)ddnew=ddnew[-tmp.vv.rm,] * tmp.nn=nchar(ddnew[,2]) * tmp.vv=which(tmp.nn>=10 & tmp.nn<=24) * #tmp.vv=which(tmp.nn>=1) * ddnew=ddnew[tmp.vv,] * ddnew=ddnew[which(ddnew[,6]!='unresolved'),] * ddnew=ddnew[grep('^C.+[FV]$',ddnew[,2]),] * #ss=sum(ddnew[,3]) * #ddnew[,4]=ddnew[,3]/ss * ddnew=ddnew[order(ddnew[,4],decreasing=T),] * #q75=quantile(ddnew[,3],0.75) * #THR=min(ddnew[,3]+1) * #tmp.vv=which(ddnew[,3]>max(q75,THR)) * #if(length(tmp.vv)<=thr)tmp.vv=1:thr * if(nrow(ddnew)>thr)ddnew=ddnew[1:thr,c(2,6,4)] else ddnew=ddnew[,c(2,6,4)] * #ddnew=ddnew[1:5000,] * ddnew=ddnew[1:min(thr,nrow(ddnew)),] * ddnew=ProcessAdaptiveVgenes(ddnew) * ddnew=cbind(ddnew, RANK=rank(ddnew[,3])/nrow(ddnew)) * TMP=gsub('.+/TCR_peptide/data/Adaptive/','',indir) * tmp=strsplit(TMP,'/')[[1]][[1]] * ddnew=cbind(ddnew, Info=paste(tmp,ff0,sep=':')) * write.table(ddnew,file=newff,quote=F,sep='\t',row.names=F) * } * } 1. PrepareAdaptiveFile(indir,outdir,thr=10000) The data I run is downloaded from adaptiveBiotechnology. The error was:Error in [<-.data.frame(tmp, , 2, value = "*01") : replacement has 1 row, data has 0. Waht should I need to adjust now? Thanks and best regards, Linqy — Reply to this email directly, view it on GitHub<#21 (comment)>, or unsubscribe<https://github.com/notifications/unsubscribe-auth/AKWYQC45CNZ5HCMCE5XY5WD3EYAHHAVCNFSM6AAAAAB7YTKLCWVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDSOJTHA2TMOBYGQ>. You are receiving this because you were mentioned.Message ID: ***@***.***> ** This email originated from an EXTERNAL sender to CHOP. Proceed with caution when replying, opening attachments, or clicking links. Do not disclose your CHOP credentials, employee information, or protected health information to a potential hacker**.

[linqy-immune]

Hello,
This is the data. Could you please help me have a look?
adaptive.txt
Thank you so much!

[s175573]

That format is different from what we expected, which is probably why. Please see attached the standard input. Best, Bo

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________________________________ From: linqy-immune ***@***.***> Sent: Saturday, June 21, 2025 9:44 PM To: s175573/GIANA ***@***.***> Cc: Li, Bo ***@***.***>; Mention ***@***.***> Subject: [External]Re: [s175573/GIANA] UnboundLocalError: local variable 'seqHead' referenced before assignment (Issue #21) [https://avatars.githubusercontent.com/u/188452455?s=20&v=4]linqy-immune left a comment (s175573/GIANA#21)<#21 (comment)> Hello, This is the data. Could you please help me have a look? adaptive.txt<https://github.com/user-attachments/files/20850719/adaptive.txt> Thank you so much! — Reply to this email directly, view it on GitHub<#21 (comment)>, or unsubscribe<https://github.com/notifications/unsubscribe-auth/AKWYQC2YTRZLQOFMI4EKSBL3EYC6NAVCNFSM6AAAAAB7YTKLCWVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDSOJTHA3DSMBRGU>. You are receiving this because you were mentioned.Message ID: ***@***.***> ** This email originated from an EXTERNAL sender to CHOP. Proceed with caution when replying, opening attachments, or clicking links. Do not disclose your CHOP credentials, employee information, or protected health information to a potential hacker**.