crlmm swMATH ID: 24830 Software Authors: Robert Scharpf; Rafael Irizarry; Matthew Ritchie; Benilton Carvalho; Ingo Ruczinski Description: Using the R Package crlmm for Genotyping and Copy Number Estimation. 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. Homepage: https://bioconductor.riken.jp/packages/3.1/bioc/html/crlmm.html Dependencies: R Keywords: copy number; batch effects; robust; multilevel model; high-throughput; oligonucleotide array; Bioconductor; R package; Journal of Statistical Software Related Software: R; GenCall; GenoSNP; GenomeStudio; mclust; SNPMClust; snow; DNAcopy; VanillaICE; lattice; cacheSweave; IRanges; Genefilter; oligoClasses; ff; Bioconductor; PLASQ; CARAT Cited in: 1 Publication Standard Articles 1 Publication describing the Software Year Cited by 5 Authors 1 Carvalho, Benilton 1 Chakravarti, Aravinda 1 Doan, Betty 1 Ruczinski, Ingo 1 Scharpf, Robert B. Cited in 1 Serial 1 Biostatistics Cited in 1 Field 1 Statistics (62-XX) Citations by Year