CNVRanger: association analysis of CNVs with gene expression and quantitative phenotypes

Vinicius da Silva; Marcel Ramos; Martien Groenen; Richard Crooijmans; Anna Johansson; Luciana Regitano; Luiz Coutinho; Ralf Zimmer; Levi Waldron; Ludwig Geistlinger

doi:10.1093/bioinformatics/btz632

CNVRanger: association analysis of CNVs with gene expression and quantitative phenotypes

Vinicius da Silva, Marcel Ramos, Martien Groenen, Richard Crooijmans, Anna Johansson, Luciana Regitano, Luiz Coutinho, Ralf Zimmer, Levi Waldron, Ludwig Geistlinger^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

19 Citations (Scopus)

Abstract

SUMMARY: 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. AVAILABILITY AND IMPLEMENTATION: http://bioconductor.org/packages/CNVRanger.

Original language	English
Pages (from-to)	972-973
Number of pages	2
Journal	Bioinformatics (Oxford, England)
Volume	36
Issue number	3
DOIs	https://doi.org/10.1093/bioinformatics/btz632
Publication status	Published - 1 Feb 2020

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title = "CNVRanger: association analysis of CNVs with gene expression and quantitative phenotypes",

abstract = "SUMMARY: 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. AVAILABILITY AND IMPLEMENTATION: http://bioconductor.org/packages/CNVRanger.",

author = "{da Silva}, Vinicius and Marcel Ramos and Martien Groenen and Richard Crooijmans and Anna Johansson and Luciana Regitano and Luiz Coutinho and Ralf Zimmer and Levi Waldron and Ludwig Geistlinger",

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doi = "10.1093/bioinformatics/btz632",

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T1 - CNVRanger: association analysis of CNVs with gene expression and quantitative phenotypes

AU - da Silva, Vinicius

AU - Ramos, Marcel

AU - Groenen, Martien

AU - Crooijmans, Richard

AU - Johansson, Anna

AU - Regitano, Luciana

AU - Coutinho, Luiz

AU - Zimmer, Ralf

AU - Waldron, Levi

AU - Geistlinger, Ludwig

PY - 2020/2/1

Y1 - 2020/2/1

N2 - SUMMARY: 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. AVAILABILITY AND IMPLEMENTATION: http://bioconductor.org/packages/CNVRanger.

AB - SUMMARY: 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. AVAILABILITY AND IMPLEMENTATION: http://bioconductor.org/packages/CNVRanger.

U2 - 10.1093/bioinformatics/btz632

DO - 10.1093/bioinformatics/btz632

M3 - Article

C2 - 31392308

AN - SCOPUS:85079077235

SN - 1367-4803

VL - 36

SP - 972

EP - 973

JO - Bioinformatics (Oxford, England)

JF - Bioinformatics (Oxford, England)

IS - 3

ER -

CNVRanger: association analysis of CNVs with gene expression and quantitative phenotypes

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