Precise inference of copy number alterations in tumor samples from SNP arrays.

ABSTRACT:

Motivation

The accurate detection of copy number alterations (CNAs) in human genomes is important for understanding susceptibility to cancer and mechanisms of tumor progression. CNA detection in tumors from single nucleotide polymorphism (SNP) genotyping arrays is a challenging problem due to phenomena such as aneuploidy, stromal contamination, genomic waves and intra-tumor heterogeneity, issues that leading methods do not optimally address.

Results

Here we introduce methods and software (PennCNV-tumor) for fast and accurate CNA detection using signal intensity data from SNP genotyping arrays. We estimate stromal contamination by applying a maximum likelihood approach over multiple discrete genomic intervals. By conditioning on signal intensity across the genome, our method

SUBMITTER: Chen GK 

PROVIDER: S-EPMC3834792 | biostudies-literature | 2013 Dec

REPOSITORIES: biostudies-literature