MathOnco / NeoPredPipe

Neoantigens prediction pipeline for multi- or single-region vcf files using ANNOVAR and netMHCpan.
GNU Lesser General Public License v3.0
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nothing in TestRun.neoantigens.txt #10

Closed axiba053 closed 5 years ago

axiba053 commented 5 years ago

Dear developers,

Thank you very much for the useful tool. I built Python2.7 with conda, and configure the 'usr_path.ini' file for my environment. Then I run python NeoPredPipe.py -I ./Example/input_vcfs -H ./Example/HLAtypes/hlatypes.txt -o ./ -n TestRun -c 1 2 -E 8 9 10.It looks like this:

INFO: Annovar reference files of build hg19 were given, using this build for all analysis.
INFO: Begin.
INFO: Running convert2annovar.py on ./Example/input_vcfs/test1.vcf
INFO: VCF Conversion Process complete ./Example/input_vcfs/test1.vcf
INFO: Running annotate_variation.pl on ./avready/test1.avinput
INFO: ANNOVAR annotation Process complete for ./avready/test1.avinput
INFO: Running coding_change.pl on ./avannotated/test1.avannotated.exonic_variant_function
INFO: Coding predictions complete for ./avannotated/test1.avannotated.exonic_variant_function
INFO: Predicting neoantigens for test1
INFO: Skipping Sample! No peptides to predict for test1
INFO: Running Epitope Predictions for test1 on epitopes of length 9
INFO: Running Epitope Predictions for test1 on epitopes of length 8
INFO: Skipping Sample! No peptides to predict for test1
INFO: Running Epitope Predictions for test1 on epitopes of length 10
INFO: Skipping Sample! No peptides to predict for test1
INFO: Predictions complete for test1 on epitopes of length 10.Indels
INFO: Digesting neoantigens for test1
INFO: Digesting neoantigens for test1
INFO: Digesting neoantigens for test1
INFO: Object size of neoantigens: 72 Kb
INFO: Running convert2annovar.py on ./Example/input_vcfs/test2.vcf
INFO: VCF Conversion Process complete ./Example/input_vcfs/test2.vcf
INFO: Running annotate_variation.pl on ./avready/test2.avinput
INFO: ANNOVAR annotation Process complete for ./avready/test2.avinput
INFO: Running coding_change.pl on ./avannotated/test2.avannotated.exonic_variant_function
INFO: Coding predictions complete for ./avannotated/test2.avannotated.exonic_variant_function
INFO: Predicting neoantigens for test2
INFO: Skipping Sample! No peptides to predict for test2
INFO: Running Epitope Predictions for test2 on epitopes of length 9
INFO: Running Epitope Predictions for test2 on epitopes of length 8
INFO: Skipping Sample! No peptides to predict for test2
INFO: Running Epitope Predictions for test2 on epitopes of length 10
INFO: Skipping Sample! No peptides to predict for test2
INFO: Predictions complete for test2 on epitopes of length 10.Indels
INFO: Digesting neoantigens for test2
INFO: Digesting neoantigens for test2
INFO: Digesting neoantigens for test2
INFO: Object size of neoantigens: 72 Kb
INFO: Summary Tables Complete.
INFO: Summary Tables Complete.
INFO: Complete

But the result I got is empty:

rw-rw-r-- 1 xueqiang.liu xueqiang.liu  223 6月  14 16:43 TestRun.neoantigens.Indels.summarytable.txt
-rw-rw-r-- 1 xueqiang.liu xueqiang.liu    0 6月  14 16:43 TestRun.neoantigens.Indels.txt
-rw-rw-r-- 1 xueqiang.liu xueqiang.liu  307 6月  14 16:43 TestRun.neoantigens.summarytable.txt
-rw-rw-r-- 1 xueqiang.liu xueqiang.liu    0 6月  14 16:43 TestRun.neoantigens.txt

And I got the same empty result with my true data.

INFO: Annovar reference files of build hg19 were given, using this build for all analysis.
INFO: Begin.
INFO: Running convert2annovar.py on ./test-lxq/vcf/test.vcf
INFO: VCF Conversion Process complete ./test-lxq/vcf/test.vcf
INFO: Running annotate_variation.pl on ./avready/test.avinput
INFO: ANNOVAR annotation Process complete for ./avready/test.avinput
INFO: Running coding_change.pl on ./avannotated/test.avannotated.exonic_variant_function
INFO: Coding predictions complete for ./avannotated/test.avannotated.exonic_variant_function
INFO: Predicting neoantigens for test
INFO: Running Epitope Predictions for test on epitopes of length 9.Indels
INFO: Running Epitope Predictions for test on epitopes of length 9
INFO: Running Epitope Predictions for test on epitopes of length 8
INFO: Running Epitope Predictions for test on epitopes of length 8.Indels
INFO: Running Epitope Predictions for test on epitopes of length 10
INFO: Running Epitope Predictions for test on epitopes of length 10.Indels
INFO: Predictions complete for test on epitopes of length 10.Indels
INFO: Digesting neoantigens for test
INFO: Digesting neoantigens for test
INFO: Digesting neoantigens for test
INFO: Object size of neoantigens: 72 Kb
INFO: Digesting neoantigens for test
INFO: Digesting neoantigens for test
INFO: Digesting neoantigens for test
INFO: Object size of neoantigens: 72 Kb
INFO: Summary Tables Complete.
INFO: Summary Tables Complete.
INFO: Complete
-rw-rw-r-- 1 xueqiang.liu xueqiang.liu  207 6月  14 17:00 Testlxq.neoantigens.Indels.summarytable.txt
-rw-rw-r-- 1 xueqiang.liu xueqiang.liu    0 6月  14 17:00 Testlxq.neoantigens.Indels.txt
-rw-rw-r-- 1 xueqiang.liu xueqiang.liu  207 6月  14 17:00 Testlxq.neoantigens.summarytable.txt
-rw-rw-r-- 1 xueqiang.liu xueqiang.liu    0 6月  14 17:00 Testlxq.neoantigens.txt

Can you tell me why and how fix it?

Best regards, xueqiangliu

elakatos commented 5 years ago

Hi!

My guess would be that there is a problem with your netMHCpan installation/set-up: getting "Object size of neoantigens: 72 Kb" basically means you had no neoantigens read in from the corresponding netMHCpan output file. If you run the example line with the '-d' flag, you can check 'tmp/test1.epitopes.X.txt' in your output folder to see the output produced by netMHCpan. It should be the input arguments to netMHCpan and whatever error line it produced if it failed.

axiba053 commented 5 years ago
# /data/biosoft/netMHCpan-4.0/Linux_x86_64/bin/netMHCpan -BA -l 8 -a HLA-B50:01,HLA-B40:01,HLA-A02:01,HLA-C06:02,HLA-C03:04,HLA-A31:01 -f ./fastaFiles/test1.tmp.8.fasta
# Fri Jun 14 17:45:13 2019
# User: xueqiang.liu
# PWD : /home/xueqiang.liu/softwares/NeoPredPipe
# Host: Linux longzhao 3.10.0-693.el7.x86_64 x86_64
# -BA      1                    Make Binding affinity prediction
# -l       8                    Peptide length [8-11] (multiple length with ,)
# -a       HLA-B50:01,HLA-B40:01,HLA-A02:01,HLA-C06:02,HLA-C03:04,HLA-A31:01 HLA allele
# -f       ./fastaFiles/test1.tmp.8.fasta File name with input
# Command line parameters set to:
#       [-rdir filename]     /data/biosoft/netMHCpan-4.0/Linux_x86_64 Home directory for NetMHpan
#       [-syn filename]      /data/biosoft/netMHCpan-4.0/Linux_x86_64/data/synlist.bin Synaps file
#       [-v]                 0                    Verbose mode
#       [-dirty]             0                    Dirty mode, leave tmp dir+files
#       [-tdir filename]     /data/biosoft/netMHCpan-4.0/tmp/netMHCpanXXXXXX Temporary directory (made with mkdtemp)
#       [-hlapseudo filename] /data/biosoft/netMHCpan-4.0/Linux_x86_64/data/MHC_pseudo.dat File with HLA pseudo sequences
#       [-hlaseq filename]                        File with full length HLA sequences
#       [-a line]            HLA-B50:01,HLA-B40:01,HLA-A02:01,HLA-C06:02,HLA-C03:04,HLA-A31:01 HLA allele
#       [-f filename]        ./fastaFiles/test1.tmp.8.fasta File name with input
#       [-w]                 0                    w option for webface
#       [-s]                 0                    Sort output on descending affinity
#       [-p]                 0                    Use peptide input
#       [-rth float]         0.500000             Rank Threshold for high binding peptides
#       [-rlt float]         2.000000             Rank Threshold for low binding peptides
#       [-l string]          8                    Peptide length [8-11] (multiple length with ,)
#       [-xls]               0                    Save output to xls file
#       [-xlsfile filename]  NetMHCpan_out.xls    Filename for xls dump
#       [-t float]           -99.900002           Threshold for output
#       [-thrfmt filename]   /data/biosoft/netMHCpan-4.0/Linux_x86_64/data/threshold/%s.thr.%s Format for threshold filenames
#       [-expfix]            0                    Exclude prefix from synlist
#       [-version filename]  /data/biosoft/netMHCpan-4.0/Linux_x86_64/data/version File with version information
#       [-inptype int]       0                    Input type [0] FASTA [1] Peptide
#       [-listMHC]           0                    Print list of alleles included in netMHCpan
#       [-allname filename]  /data/biosoft/netMHCpan-4.0/Linux_x86_64/data/allelenames File with print names for alleles
#       [-BA]                1                    Make Binding affinity prediction

# NetMHCpan version 4.0

Error. Cannot make tmpdir. Exit

yes !there is something wrong. I do not know the path to make tmpdir...

elakatos commented 5 years ago

Hi! This is something specific to your own system, so I am not sure the advice I can give is appropriate for your case. In the netMHCpan executable file (I guess in your system the path is /data/biosoft/netMHCpan-4.0/netMHCpan ) you should change the line "setenv TMPDIR /your/path/to/tmpdir" to somewhere which definitely exists and the system has writing privileges there. So if it is set to "/data/biosoft/netMHCpan-4.0/tmp", then make sure that you have a directory called "tmp" inside the netMHCpan folder, and maybe set it's privileges (chmod 777 tmp) to be sure new temporary folder can be created inside it.

axiba053 commented 5 years ago

thank you for your help! the problem has been solved.