reGenotyper: Detecting mislabeled samples in genetic data
Zych, Konrad; Snoek, Basten L.; Elvin, Mark; Rodriguez, Miriam; Van der Velde, K. Joeri; Arends, Danny; Westra, Harm-Jan; Swertz, Morris A.; Poulin, Gino; Kammenga, Jan E.; Breitling, Rainer; Jansen, Ritsert C.; Li, Yang
In high-throughput molecular profiling studies, genotype labels can be wrongly assigned at various experimental steps; the resulting mislabeled samples seriously reduce the power to detect the genetic basis of phenotypic variation. We have developed an approach to detect potential mislabeling, recover the “ideal” genotype and identify “best-matched” labels for mislabeled samples. On average, we identified 4% of samples as mislabeled in eight published datasets, highlighting the necessity of applying a “data cleaning” step before standard data analysis.
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Biology and Life Sciences; Computational Biology; Genome Analysis; Genome-Wide Association Studies; Genetics; Genomics; Human Genetics; Evolutionary Biology; Population Genetics; Genetic Polymorphism; Population Biology; Phenotypes; Genetic Loci; Quantitative Trait Loci; Gene Expression; Physical Sciences; Mathematics; Discrete Mathematics; Combinatorics; Permutation; Experimental Organism Systems; Model Organisms; Caenorhabditis Elegans; Animal Models; Organisms; Animals; Invertebrates; Nematoda; Caenorhabditis