Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Rebecca Killick, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: Robert B. Scharpf, Rafael A. Irizarry, Matthew E. Ritchie, Benilton Carvalho, Ingo Ruczinski
Title: Using the R Package crlmm for Genotyping and Copy Number Estimation
Abstract: Genotyping platforms such as Affymetrix can be used to assess genotype-phenotype as well as copy number-phenotype associations at millions of markers. While genotyping algorithms are largely concordant when assessed on HapMap samples, tools to assess copy number changes are more variable and often discordant. One explanation for the discordance is that copy number estimates are susceptible to systematic differences between groups of samples that were processed at different times or by different labs. Analysis algorithms that do not adjust for batch effects are prone to spurious measures of association. The R package crlmm implements a multilevel model that adjusts for batch effects and provides allele-specific estimates of copy number. This paper illustrates a workflow for the estimation of allele-specific copy number and integration of the marker-level estimates with complimentary Bioconductor software for inferring regions of copy number gain or loss. All analyses are performed in the statistical environment R.

Page views:: 8981. Submitted: 2010-09-09. Published: 2011-05-02.
Paper: Using the R Package crlmm for Genotyping and Copy Number Estimation     Download PDF (Downloads: 8566)
crlmm_1.10.0.tar.gz: R source package Download (Downloads: 586; 2MB)
crlmmCompendium_1.1.0.tar.gz: R source package with compendium for replication Download (Downloads: 2578; 7MB)
v40i12.R: R example code from the paper Download (Downloads: 696; 5KB)

DOI: 10.18637/jss.v040.i12

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.