Best algorithms for case-control study?

[XMarc3ll]

I'm working on a case-control study with exome sequencing data, trying to find CNVs linked to a specific disease. I've been looking into various CNV calling algorithms for exome data. I read GATK gCNV, ExomeDepth, and cn.MOPS are among the top options but I'm curious to know if anyone here has used other algorithms. What would you recommend if I'm primarily after the detection of exome CNVs?

 

[X-Man]

I'm working on a case-control study with exome sequencing data, trying to find CNVs linked to a specific disease. I've been looking into various CNV calling algorithms for exome data. I read GATK gCNV, ExomeDepth, and cn.MOPS are among the top options but I'm curious to know if anyone here has used other algorithms. What would you recommend if I'm primarily after the detection of exome CNVs?

I have used XHMM in the past. My opinion is it is a little clunky to set up but it is alright for rare CNVs. That said, gCNV from GATK has been my favorite lately, especially if you're already in their ecosystem.

 

[Low_Local26]

Nice work diving into CNV detection! XHMM's good but you might also want to check out CLAMMS, and CoNIFER, they're also good for exome data and have been used in large-scale studies.

 

[st3@k to_go]

I have used XHMM in the past. My opinion is it is a little clunky to set up but it is alright for rare CNVs. That said, gCNV from GATK has been my favorite lately, especially if you're already in their ecosystem.

yeah, for case control, XHMM is a fantastic choice, especially for finding rare CNVs. It models the data across samples to account for batch effects, which is crucial for studies like yours