title: Influence analysis in quantitative trait loci detection.
abstract: This paper presents systematic methods for the detection of influential individuals that affect the log odds (LOD) score curve. We derive general formulas of influence functions for profile likelihoods and introduce them into two standard quantitative trait locus detection methods-the interval mapping method and single marker analysis. Besides influence analysis on specific LOD scores, we also develop influence analysis methods on the shape of the LOD score curves. A simulation-based method is proposed to assess the significance of the influence of the individuals. These methods are shown useful in the influence analysis of a real dataset of an experimental population from an F2 mouse cross. By receiver operating characteristic analysis, we confirm that the proposed methods show better performance than existing diagnostics.
authors.affiliation: The Institute of Statistical Mathematics, Research Organization of Information and Systems, 10-3 Midori-cho, Tachikawa, Tokyo, 190-8562, Japan.
authors.forename: Xiaoling
authors.initials: X
authors.lastname: Dou
authors.forename: Satoshi
authors.initials: S
authors.lastname: Kuriki
authors.forename: Akiteru
authors.initials: A
authors.lastname: Maeno
authors.forename: Toyoyuki
authors.initials: T
authors.lastname: Takada
authors.forename: Toshihiko
authors.initials: T
authors.lastname: Shiroishi
mesh_terms: D000818:Animals; D001699:Biometry / Q000379:methods*; D002874:Chromosome Mapping / Q000379:methods*; D033481:Chromosomes, Mammalian / Q000235:genetics; D016013:Likelihood Functions; D051379:Mice; D015233:Models, Statistical; D040641:Quantitative Trait Loci / Q000235:genetics*; D012372:ROC Curve
keywords: Influence score vector; Profile likelihood; ROC analysis; Shape of LOD score curve; Standardized empirical influence function
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