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Large deletion filtered out #479

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sumudu-rangika opened this issue May 10, 2024 · 3 comments
Open

Large deletion filtered out #479

sumudu-rangika opened this issue May 10, 2024 · 3 comments
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@sumudu-rangika
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sumudu-rangika commented May 10, 2024

Hi,

Thank you for a great tool!

My question is, in one of my samples there are two deletions near each other. One is ~2847bp and other is ~12150bp (one copy of CYP2D6 gene deletion). These two deletions are clearly visualized in IGV (attached). The small ~2847 deletion is called as a filter PASS SV with GT=1 | 0, GQ=47, DR=19 and DV=10. The large deletion which is close by has been called as a PRECISE SV but has been filtered with GT. This variant has a GT=0 | 0, GQ=26, DV=4 while the DR=24. But in the IGV image there are 11 reads that supports this large deletion. Why is sniffles calculate it as 4? I believe this is the reason for it to get filtered with GT as the GQ is high (screen shot attached). The small deletion and large deletions are on the same reads. But small is PASS and large is filtered.

Also, in another sample there's a filter PASS variant called as ./. genotype.

This is ONT WGS data. Please help me to understand this.

Thank you
Best
Sumudu

deletion.pdf
Screenshot from 2024-05-10 16-21-34

@lfpaulin
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Hello Sumudu
It looks like Sniffles is only using the reads marked in red for that call. Can you confirm it with the read names you have in the INFO field under RNAMES
It seems that the other reads were not used, likely based on position. We would like to investigate further that issue. Could you please run the sample again and adding the --no-qc flag and sharing the output SVs that are in that region. It could be only columns 1,2,3,7,8 and 10 from the VCF file
image

Best
Luis

@sumudu-rangika
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Hi Luis,

Many Thanks for your feedback.

As you said the RNAMES are the ones you marked in red. And I tried with the --no-qc option with sniffles 2.3.3 latest version. It detects the large (~12, 150bp) deletion. But VCF has more than one entry for the same deletion with different RNAMES. I attached here the extracted region of interest in a .txt file for your reference.
In this case, what would be the best way to run sniffles? Greatly appreciate your help to understand this.

I also have hybrid SVs in CYP2D6 gene that represent as insertion which I'm trying to figure out. I'll post it as a separate issue.

Thank you
Best
Sumudu
test.txt

@lfpaulin lfpaulin self-assigned this Nov 6, 2024
@lfpaulin
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lfpaulin commented Nov 6, 2024

Dear Sumudu,

here are some insights:

  1. the PASS variant (left to the 12.5kb ones) is clearly shown in the blue haplotype
  2. the 12.5kb DEL has a GT filter given the support reads (4) is not enough to assign a genotype
  3. for the remaining six SVs that have the DEL, it is likely that the clustering algorithm we use is not making them a single SV given they have different start positions (up to 1kb difference)

We are about to release a new version (2.5) which improves the detection of DEL, could you please run you sample with the new version (will be out in a couple of days)

chr22	42117822	Sniffles2.DEL.E9ES25	PASS	PRECISE;SVTYPE=DEL;SVLEN=-2847;END=42120669;SUPPORT=10
chr22	42125646	Sniffles2.DEL.EA4S25	GT	PRECISE;SVTYPE=DEL;SVLEN=-12150;END=42137796;SUPPORT=4
chr22	42124282	Sniffles2.DEL.E9FS25	SUPPORT_MIN	PRECISE;SVTYPE=DEL;SVLEN=-12150;END=42136432;SUPPORT=1
chr22	42124530	Sniffles2.DEL.EA0S25	SUPPORT_MIN	PRECISE;SVTYPE=DEL;SVLEN=-12141;END=42136671;SUPPORT=1
chr22	42124650	Sniffles2.DEL.EA1S25	SUPPORT_MIN	PRECISE;SVTYPE=DEL;SVLEN=-12155;END=42136805;SUPPORT=1
chr22	42124957	Sniffles2.DEL.EA2S25	SUPPORT_MIN	PRECISE;SVTYPE=DEL;SVLEN=-12150;END=42137107;SUPPORT=1
chr22	42125268	Sniffles2.DEL.EA3S25	SUPPORT_MIN	PRECISE;SVTYPE=DEL;SVLEN=-12150;END=42137418;SUPPORT=2
chr22	42125886	Sniffles2.DEL.EA5S25	SUPPORT_MIN	PRECISE;SVTYPE=DEL;SVLEN=-12149;END=42138035;SUPPORT=1

Best
Luis

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