CNVcaller: highly efficient and widely applicable software for detecting copy number variations in large populations.

ABSTRACT:

Background

The increasing amount of sequencing data available for a wide variety of species can be theoretically used for detecting copy number variations (CNVs) at the population level. However, the growing sample sizes and the divergent complexity of nonhuman genomes challenge the efficiency and robustness of current human-oriented CNV detection methods.

Results

Here, we present CNVcaller, a read-depth method for discovering CNVs in population sequencing data. The computational speed of CNVcaller was 1-2 orders of magnitude faster than CNVnator and Genome STRiP for complex genomes with thousands of unmapped scaffolds. CNV detection of 232 goats required only 1.4 days on a single compute node. Additionally, the Mendelian consistency of sheep trios indicated that CNVcaller m

SUBMITTER: Wang X 

PROVIDER: S-EPMC5751039 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature