title: Variable-Selection Emerges on Top in Empirical Comparison of Whole-Genome Complex-Trait Prediction Methods.
abstract: Accurate prediction of complex traits based on whole-genome data is a computational problem of paramount importance, particularly to plant and animal breeders. However, the number of genetic markers is typically orders of magnitude larger than the number of samples (p >> n), amongst other challenges. We assessed the effectiveness of a diverse set of state-of-the-art methods on publicly accessible real data. The most surprising finding was that approaches with feature selection performed better than others on average, in contrast to the expectation in the community that variable selection is mostly ineffective, i.e. that it does not improve accuracy of prediction, in spite of p >> n. We observed superior performance despite a somewhat simplistic approach to variable selection, possibly suggesting an inherent robustness. This bodes well in general since the variable selection methods usually improve interpretability without loss of prediction power. Apart from identifying a set of benchmark data sets (including one simulated data), we also discuss the performance analysis for each data set in terms of the input characteristics.
authors.affiliation: Computational Biology Center, IBM T. J. Watson Research, Yorktown Heights, NY 10598, United States of America.
authors.forename: David C
authors.initials: DC
authors.lastname: Haws
authors.affiliation: Computational Biology Center, IBM T. J. Watson Research, Yorktown Heights, NY 10598, United States of America.
authors.forename: Irina
authors.initials: I
authors.lastname: Rish
authors.affiliation: Limagrain Europe, Centre de Recherche de Chappes, CS 3911, Route d'Ennezat, Chappes 63720, France.
authors.forename: Simon
authors.initials: S
authors.lastname: Teyssedre
authors.affiliation: Computational Biology Center, IBM T. J. Watson Research, Yorktown Heights, NY 10598, United States of America.
authors.forename: Dan
authors.initials: D
authors.lastname: He
authors.affiliation: Business Analytics and Mathematical Sciences Department, IBM T. J. Watson Research, Yorktown Heights, NY 10598, United States of America.
authors.forename: Aurelie C
authors.initials: AC
authors.lastname: Lozano
authors.affiliation: Business Analytics and Mathematical Sciences Department, IBM T. J. Watson Research, Yorktown Heights, NY 10598, United States of America.
authors.forename: Prabhanjan
authors.initials: P
authors.lastname: Kambadur
authors.affiliation: Limagrain Europe, Centre de Recherche de Chappes, CS 3911, Route d'Ennezat, Chappes 63720, France.
authors.forename: Zivan
authors.initials: Z
authors.lastname: Karaman
authors.affiliation: Computational Biology Center, IBM T. J. Watson Research, Yorktown Heights, NY 10598, United States of America.
authors.forename: Laxmi
authors.initials: L
authors.lastname: Parida
mesh_terms: D000465:Algorithms; D000818:Animals; D005819:Genetic Markers / Q000235:genetics*; D016678:Genome / Q000235:genetics; D008957:Models, Genetic; D040641:Quantitative Trait Loci / Q000235:genetics*; D013552:Swine; D003313:Zea mays / Q000235:genetics
chemical_list: D005819:Genetic Markers