Using the r package crlmm for genotyping and copy number estimation

Robert B. Scharpf, Rafael A. Irizarry, Matthew E. Ritchie, Benilton Carvalho, Ingo Ruczinski

Research output: Contribution to journalArticlepeer-review

45 Scopus citations


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-speciffc estimates of copy number. This paper illustrates a workow for the estimation of allele-speciffc 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.

Original languageEnglish (US)
Pages (from-to)1-32
Number of pages32
JournalJournal of Statistical Software
Issue number12
StatePublished - 2011


  • Batch effects
  • Copy number
  • High-throughput
  • Multilevel model
  • Oligonucleotide array
  • Robust

ASJC Scopus subject areas

  • Software
  • Statistics and Probability
  • Statistics, Probability and Uncertainty


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