IgC2N is a three step computational framework to discover and genotype germline CNVs. First, we detect candidate CNV loci by combining information across multiple samples without imposing restrictions to the number of coverage markers or to the variant size. Secondly, we fine tune the detection of rare variants and infer the putative copy number classes for each locus. Last, for each variant we combine the relative distance between consecutive copy number classes with genetic information in a novel attempt to estimate the reference model bias.
Banerjee S, Oldridge D, Poptsova M, Hussain WM, Chakravarty D, Demichelis F. A computational framework discovers new copy number variants with functional importance. PLoS One. 2011 Mar 29;6(3):e17539.
Demichelis F, Setlur SR et al, Identification of functionally active, low frequency copy numbervariants at 15q21.3 and 12q21.31 associated with prostate cancer risk. Proc Natl Acad Sci U S A. 2012 Apr 24;109(17):6686-91.