Hello,
I have a multi sample vcf with affected and unaffected samples. Usually i remove variant absent in affected samples After annotations and conversion of vcf to rdv file, through a python script, but it's a bit useless to annotate all these variants to remove it immediatly After.
So i'm searching a tool to filter directly the vcf before annotations. I look on bcftools or vcftools but i didn't find the option for what i want.
•
written
by
quentin54520 •
using vcffilterjdk http://lindenb.github.io/jvarkit/VcfFilterJdk.html
java -jar dist/vcffilterjdk.jar -e ' final List<String> controls = Arrays.asList("S1","S2","S3","S4"); return controls.stream().map(S->variant.getGenotype(S)).noneMatch(G->G.isHet() || G.isHomVar());' in.vcf
Thank you for your reply. I'm not sure I understand the command, I have to replace the ("S1","S2","S3","S4") by the list of my unaffected samples?
by the list of my unaffected samples?
yes
Unfortunately when i try to install it with:
git clone "https://github.com/lindenb/jvarkit.git"
cd jvarkit
./gradlew vcffilterjdk
i get the error:
Exception in thread "main" java.lang.RuntimeException: Could not create parent directory for lock file /shared/home/quentin67100/.gradle/wrapper/dists/gradle-6.7-bin/efvqh8uyq79v2n7rcncuhu9sv/gradle-6.7-bin.zip.lck at org.gradle.wrapper.ExclusiveFileAccessManager.access(ExclusiveFileAccessManager.java:43) at org.gradle.wrapper.Install.createDist(Install.java:48) at org.gradle.wrapper.WrapperExecutor.execute(WrapperExecutor.java:107) at org.gradle.wrapper.GradleWrapperMain.main(GradleWrapperMain.java:63)
do you have the right to create directories under /shared/home/quentin67100/.gradle ?
You're right, it's an issue with space disk quota on my home.
It sounds like you are already familiar with Python, so here's one solution using the pyvcf submodule from the fuc package I wrote.
Let's imagine you have 3 controls (C1-C3) and 3 affected samples (A1-A3).
>>> from fuc import pyvcf
>>> data = {
... 'CHROM': ['chr1', 'chr1', 'chr1'],
... 'POS': [100, 101, 102],
... 'ID': ['.', '.', '.'],
... 'REF': ['G', 'T', 'T'],
... 'ALT': ['A', 'C', 'A'],
... 'QUAL': ['.', '.', '.'],
... 'FILTER': ['.', '.', '.'],
... 'INFO': ['.', '.', '.'],
... 'FORMAT': ['GT', 'GT', 'GT'],
... 'C1': ['0/1', '0/1', '0/0'],
... 'C2': ['0/0', '1/1', '0/0'],
... 'C3': ['0/1', '0/1', '0/0'],
... 'A1': ['0/0', '0/1', '1/1'],
... 'A2': ['0/0', '1/1', '0/1'],
... 'A3': ['0/0', '0/0', '0/1'],
... }
>>> vf = pyvcf.VcfFrame.from_dict([], data)
>>> # vf = pyvcf.VcfFrame.from_file('in.vcf')
>>> vf.df
CHROM POS ID REF ALT QUAL FILTER INFO FORMAT C1 C2 C3 A1 A2 A3
0 chr1 100 . G A . . . GT 0/1 0/0 0/1 0/0 0/0 0/0
1 chr1 101 . T C . . . GT 0/1 1/1 0/1 0/1 1/1 0/0
2 chr1 102 . T A . . . GT 0/0 0/0 0/0 1/1 0/1 0/1
You can remove variants that are absent in the affected.
>>> filtered_vf = vf.filter_sampany(['A1', 'A2', 'A3'])
>>> filtered_vf.df
CHROM POS ID REF ALT QUAL FILTER INFO FORMAT C1 C2 C3 A1 A2 A3
0 chr1 101 . T C . . . GT 0/1 1/1 0/1 0/1 1/1 0/0
1 chr1 102 . T A . . . GT 0/0 0/0 0/0 1/1 0/1 0/1
Optionally write the VCF data to an output file.
# filtered_vf.to_file('out.vcf')
Let me know if you have any questions.
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