title: An evaluation of methods correcting for cell-type heterogeneity in DNA methylation studies.
abstract: BACKGROUND
  Many different methods exist to adjust for variability in cell-type mixture proportions when analyzing DNA methylation studies. Here we present the result of an extensive simulation study, built on cell-separated DNA methylation profiles from Illumina Infinium 450K methylation data, to compare the performance of eight methods including the most commonly used approaches.
  
  
  RESULTS
  We designed a rich multi-layered simulation containing a set of probes with true associations with either binary or continuous phenotypes, confounding by cell type, variability in means and standard deviations for population parameters, additional variability at the level of an individual cell-type-specific sample, and variability in the mixture proportions across samples. Performance varied quite substantially across methods and simulations. In particular, the number of false positives was sometimes unrealistically high, indicating limited ability to discriminate the true signals from those appearing significant through confounding. Methods that filtered probes had consequently poor power. QQ plots of p values across all tested probes showed that adjustments did not always improve the distribution. The same methods were used to examine associations between smoking and methylation data from a case-control study of colorectal cancer, and we also explored the effect of cell-type adjustments on associations between rheumatoid arthritis cases and controls.
  
  
  CONCLUSIONS
  We recommend surrogate variable analysis for cell-type mixture adjustment since performance was stable under all our simulated scenarios.
authors.affiliation: McGill University, Department of Epidemiology, Biostatistics, and Occupational Health, 1020 Pine Ave. West, Montréal, H3A 1A2, QC, Canada.|Lady Davis Research Institute, Jewish General Hospital, 3755 Chemin de la Côte Sainte Catherine, Montréal, H3T 1E2, QC, Canada.
authors.forename: Kevin
authors.initials: K
authors.lastname: McGregor
authors.affiliation: Lady Davis Research Institute, Jewish General Hospital, 3755 Chemin de la Côte Sainte Catherine, Montréal, H3T 1E2, QC, Canada.
authors.forename: Sasha
authors.initials: S
authors.lastname: Bernatsky
authors.affiliation: The Research Institute of the McGill University Health Centre, Montréal, QC, Canada.
authors.forename: Ines
authors.initials: I
authors.lastname: Colmegna
authors.affiliation: Lady Davis Research Institute, Jewish General Hospital, 3755 Chemin de la Côte Sainte Catherine, Montréal, H3T 1E2, QC, Canada.|Division of Rheumatology, Jewish General Hospital, Montréal, QC, Canada.|Department of Medicine, McGill University, Montréal, QC, Canada.
authors.forename: Marie
authors.initials: M
authors.lastname: Hudson
authors.affiliation: McGill University and Genome Quebec Innovation Centre, McGill University, Montréal, QC, Canada.|Department of Human Genetics, McGill University, Montréal, QC, Canada.
authors.forename: Tomi
authors.initials: T
authors.lastname: Pastinen
authors.affiliation: McGill University, Department of Epidemiology, Biostatistics, and Occupational Health, 1020 Pine Ave. West, Montréal, H3A 1A2, QC, Canada.|Department of Psychiatry, McGill University, Montréal, QC, Canada.|The Douglas Mental Health University Institute, Verdun, QC, Canada.
authors.forename: Aurélie
authors.initials: A
authors.lastname: Labbe
authors.affiliation: Lady Davis Research Institute, Jewish General Hospital, 3755 Chemin de la Côte Sainte Catherine, Montréal, H3T 1E2, QC, Canada. celia.greenwood@mcgill.ca.
authors.forename: Celia M T
authors.initials: CM
authors.lastname: Greenwood
mesh_terms: D000465:Algorithms; D001172:Arthritis, Rheumatoid / Q000235:genetics; D016022:Case-Control Studies; D002469:Cell Separation / Q000379:methods* / Q000592:standards; D015179:Colorectal Neoplasms / Q000235:genetics; D003198:Computer Simulation; D019175:DNA Methylation; D018740:Genetic Heterogeneity; D006801:Humans; D009000:Monocytes / Q000166:cytology / Q000378:metabolism; D009928:Organ Specificity; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D017422:Sequence Analysis, DNA / Q000379:methods* / Q000592:standards
keywords: Cell-type mixture; DNA methylation; Deconvolution; Matrix decomposition