CLAMMS: a scalable algorithm for calling common and rare copy number variants from exome sequencing data.

ABSTRACT:

Motivation

Several algorithms exist for detecting copy number variants (CNVs) from human exome sequencing read depth, but previous tools have not been well suited for large population studies on the order of tens or hundreds of thousands of exomes. Their limitations include being difficult to integrate into automated variant-calling pipelines and being ill-suited for detecting common variants. To address these issues, we developed a new algorithm--Copy number estimation using Lattice-Aligned Mixture Models (CLAMMS)--which is highly scalable and suitable for detecting CNVs across the whole allele frequency spectrum.

Results

In this note, we summarize the methods and intended use-case of CLAMMS, compare it to previous algorithms and briefly describe results of validation exper

SUBMITTER: Packer JS 

PROVIDER: S-EPMC4681995 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature