Details

Autor(en) / Beteiligte

• Amarasinghe, Kaushalya C
• Li, Jason
• Hunter, Sally M
• Ryland, Georgina L
• Cowin, Prue A
• Campbell, Ian G
• Halgamuge, Saman K

Titel

Inferring copy number and genotype in tumour exome data

Ist Teil von

• BMC genomics, 2014-08, Vol.15 (1), p.732-732, Article 732

Ort / Verlag

England: BioMed Central Ltd

Erscheinungsjahr

2014

Quelle

MEDLINE

Beschreibungen/Notizen

• 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. We propose a new method to infer copy number and genotypes using whole exome data from paired tumour/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 baseline shift. Our method makes explicit detection on chromosome 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/normal exomes and evaluated the performance by comparing against the copy number variations and genotypes predicted using Affymetrix SNP 6.0 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. 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/.