Open AccessCNVRanger: association analysis of CNVs with gene expression and quantitative phenotypes
Author(s) -
Vinicius Henrique da Silva,
Marcel Ramos,
Martien A. M. Groenen,
R.P.M.A. Crooijmans,
Anna M. Johansson,
Luciana Correia de Almeida Regitano,
Luiz Lehmann Coutinho,
Ralf Zimmer,
Levi Waldron,
Ludwig Geistlinger
Publication year - 2019
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btz632
Subject(s) - bioconductor , copy number variation , biology , computational biology , structural variation , inference , phenotype , genetics , genetic association , snp array , snp , genome wide association study , gene , single nucleotide polymorphism , genome , computer science , genotype , artificial intelligence
Copy number variation (CNV) is a major type of structural genomic variation that is increasingly studied across different species for association with diseases and production traits. Established protocols for experimental detection and computational inference of CNVs from SNP array and next-generation sequencing data are available. We present the CNVRanger R/Bioconductor package which implements a comprehensive toolbox for structured downstream analysis of CNVs. This includes functionality for summarizing individual CNV calls across a population, assessing overlap with functional genomic regions, and genome-wide association analysis with gene expression and quantitative phenotypes.
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