Tuesday, September 16, 2014

Fwd: Inferring copy number and genotype in tumour exome data

Fwd: please follow footer link

Inferring copy number and genotype in tumour exome data: "Background:
Using whole exome sequencing to predict aberrations in tumours is a cost effective alternative to whole genome sequencing, however is predominantly used for variant detection and infrequently utilised for detection of somatic copy number variation.
Results:
We propose a new method to infer copy number and genotypes using whole exome data from paired tumour/matched normal samples. Our algorithm uses two Hidden Markov Models to predict copy number and genotypes and computationally resolves polyploidy/aneuploidy, normal cell contamination and signal base line shift. Our method makes explicit detection on arm level events, which are commonly found in tumour samples. The methods are combined into a package named ADTEx (Aberration Detection in Tumour Exome). We applied our algorithm to a cohort of 17 in-house generated and 18 TCGA paired ovarian cancer/ matched normal exomes and evaluated the performance by comparing against the copy number variations and genotypes predicted using Affymetrix SNP 6 data of the same samples. Further, we carried out a comparison study to show that ADTEx outperformed its competitors in terms of precision and F-measure.
Conclusions:
Our proposed method, ADTEx, uses both depth of coverage ratios and B allele frequencies calculated from whole exome sequencing data, to predict copy number variations along with their genotypes. ADTEx is implemented as a user friendly software package using python and R statistical language. Source code and sample data are freely available under GNU license (GPLv3) at http://adtex.sourceforge.net/."

(Via http://www.biomedcentral.com/1471-2164/15/732.)