identification of common CNVs

Question

[smrutimayipanda]

i need to know that i m doing identification of common CNVs using HD-CNV software by 90% reciprocal overlap. But this software considers the whole genome as CNV. Is it possible? after that, I got huge no of unique genes in that particular chromosomes, say chr1, i got 1296 genes. so how can i interpret gain, loss and mixed genes? Is there any alternative for identification of common CNV and extraction of CNV-genes?

Answer 1

[QVINTVS_FABIVS_MAXIMVS]

But this software considers the whole genome as CNV. Is it possible?

No there are regions of the genome that are copy number intolerant. Tools like GenomeStrip use this information to build a prior model

Is there any alternative for identification of common CNV and extraction of CNV-genes?

In my opinion, the best curated list of common SVs were produced by the 1000 Genomes Project. This is the paper for the release

The most recent release is here: ftp://ftp.1000genomes.ebi.ac.uk/vol1/ftp/phase3/integrated_sv_map/

You can convert the VCF into a BED file, you'll have to extract the SVTYPE= and END= entries from the INFO column to build the BED file. Note that VCFs are 1-based and BEDs are 0-based, so you'll have to subtract 1 from POS

Then you can use bedtools intersect to find reciprocally overlapping regions. You can also use bedtools intersect to overlap SVs to genes. Alternatively, you can annotate the SVs with ANNOVAR to determine which genes overlap them.

As for variant interpretation, it's harder for SVs. Deletions of exons are effectively a Loss-of-function mutation. Duplications and other SV types are harder to interpret. For example, whole-gene duplications can be less damaging than a gene with a subset of duplicated exons. One way to stratify loss of function deletions would be the pLI score of the gene(s).

Answer 2

[smrutimayipanda]

Sorry I mean to say consensus CNVs. I am working on breast cancer and need to find the consensus CNVs through this software. Please suggest me regarding this