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KELVIN: A Software Package for Rigorous Measurement of Statistical Evidence in Human GeneticsVieland V.J.a, b · Huang Y.a · Seok S.-C.a · Burian J.a · Catalyurek U.c · O’Connell J.d · Segre A.e · Valentine-Cooper W.a
aBattelle Center for Mathematical Medicine, Research Institute at Nationwide Children’s Hospital, and Departments of bPediatrics and Statistics, and cBiomedical Informatics, Ohio State University, Columbus, Ohio, dDepartment of Medicine, University of Maryland School of Medicine, Baltimore, Md., and eDepartment of Computer Science, University of Iowa, Iowa City, Iowa, USA Corresponding Author
Veronica J. Vieland, PhD
Research Institute at Nationwide Children’s Hospital
700 Children’s Drive
Columbus, OH 43205 (USA)
Tel. +1 614 355 2861, E-Mail Veronica.Vieland@nationwidechildrens.org
This paper describes the software package KELVIN, which supports the PPL (posterior probability of linkage) framework for the measurement of statistical evidence in human (or more generally, diploid) genetic studies. In terms of scope, KELVIN supports two-point (trait-marker or marker-marker) and multipoint linkage analysis, based on either sex-averaged or sex-specific genetic maps, with an option to allow for imprinting; trait-marker linkage disequilibrium (LD), or association analysis, in case-control data, trio data, and/or multiplex family data, with options for joint linkage and trait-marker LD or conditional LD given linkage; dichotomous trait, quantitative trait and quantitative trait threshold models; and certain types of gene-gene interactions and covariate effects. Features and data (pedigree) structures can be freely mixed and matched within analyses. The statistical framework is specifically tailored to accumulate evidence in a mathematically rigorous way across multiple data sets or data subsets while allowing for multiple sources of heterogeneity, and KELVIN itself utilizes sophisticated software engineering to provide a powerful and robust platform for studying the genetics of complex disorders.
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