Statistical Analysis of RIX for Complex Traits

University Of North Carolina Chapel Hill, Chapel Hill NC

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Abstract

DESCRIPTION (provided by applicant): With the recent resurgence of an emphasis on complex traits, new approaches and experimental crosses are being developed. Genes modulating the complexities of brain biology and behavioral, as well as gene environment interactions have been particularly difficult to identify. In order to overcome some of these deficiencies, we will develop simple yet accurate statistical methods for complex quantitative trait loci mapping using recently described recombinant inbred intercrosses (RIX). Thus the specific aims are to 1) Develop appropriate statistical analysis tools for the RIX design; 2) Derive appropriate significance thresholds of the test statistics empirically and theoretically; and 3) Develop open source software to implement RIX methods. The approaches we describe in this small project will greatly aid developments in complex trait dissection and should lead to greater precision and more accurate localization of the causative genes in a wide variety of research applications, not the least of which is the role of genes in neurological diseases.