Detecting common copy number variants in high-throughput sequencing data by using JointSLM algorithm.

ABSTRACT: The discovery of genomic structural variants (SVs), such as copy number variants (CNVs), is essential to understand genetic variation of human populations and complex diseases. Over recent years, the advent of new high-throughput sequencing (HTS) platforms has opened many opportunities for SVs discovery, and a very promising approach consists in measuring the depth of coverage (DOC) of reads aligned to the human reference genome. At present, few computational methods have been developed for the analysis of DOC data and all of these methods allow to analyse only one sample at time. For these reasons, we developed a novel algorithm (JointSLM) that allows to detect common CNVs among individuals by analysing DOC data from multiple samples simultaneously. We test JointSLM performance on synthet

SUBMITTER: Magi A 

PROVIDER: S-EPMC3105418 | biostudies-literature | 2011 May

REPOSITORIES: biostudies-literature