A Lasso multi-marker mixed model for association mapping with population structure correction
Author(s) -
Barbara Rakitsch,
Christoph Lippert,
Oliver Stegle,
Karsten Borgwardt
Publication year - 2012
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/bts669
Subject(s) - genetic association , genome wide association study , single nucleotide polymorphism , biology , spurious relationship , population , computational biology , confounding , quantitative trait locus , lasso (programming language) , mendelian inheritance , association mapping , genetics , locus (genetics) , multivariate statistics , genotype , computer science , statistics , gene , machine learning , mathematics , demography , sociology , world wide web
Exploring the genetic basis of heritable traits remains one of the central challenges in biomedical research. In traits with simple Mendelian architectures, single polymorphic loci explain a significant fraction of the phenotypic variability. However, many traits of interest seem to be subject to multifactorial control by groups of genetic loci. Accurate detection of such multivariate associations is non-trivial and often compromised by limited statistical power. At the same time, confounding influences, such as population structure, cause spurious association signals that result in false-positive findings.
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