Demichelis Lab - Computational Oncology

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.

• IgC2N.tar.gz The folder contains i) source codes needed to run the IgC2N pipeline (organized in the IgC2Ntest/Code_Source), ii) example data (Pre-processed Affymetrix 6.0 data on Chromosome 17 of 210 HapMap Phase 2 individulas), and iii) the README.txt file for details on how to run the IgC2N pipeline. Briefly, the pipeline can be run using the IgC2Ntest/Code_Source/IgC2N_pipeline.R code in the IgC2Ntest/ directory.

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.