Comparison of Methods to Account for Relatedness in Genome-Wide Association Studies with Family-Based Data

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Recently, statistical approaches known as linear mixed models (LMMs) have become popular for analysing data from genome-wide association studies. In the last few years, a bewildering variety of different LMM methods/software packages have been developed, but it has not always been clear how (or indeed whether) any newly-proposed method differs from previously-proposed implementations. Here we compare the performance of several different LMM approaches (and software implementations) via their application to a genome-wide association study of visceral leishmaniasis in 348 Brazilian families comprising 3626 individuals. We also compare the LMM results to those obtained using alternative analysis methods. Overall, we find strong concordance between the results from the different LMM approaches and high correlation between the results from LMMs and most alternative approaches. We conclude that LMM approaches perform well in comparison to competing approaches and, in most applications, the precise LMM implementation will not be too important, and can be chosen on the basis of speed or convenience.

Vyšlo v časopise: Comparison of Methods to Account for Relatedness in Genome-Wide Association Studies with Family-Based Data. PLoS Genet 10(7): e32767. doi:10.1371/journal.pgen.1004445
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pgen.1004445

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