Vieland Veronica J, Huang Yungui, Seok Sang-Cheol, Burian John, Catalyurek Umit, O'Connell Jeffrey, Segre Alberto, Valentine-Cooper William
Battelle Center for Mathematical Medicine, Research Institute at Nationwide Children's Hospital, Ohio State University, 700 Children’s Drive, Columbus, OH 43205, USA.
Hum Hered. 2011;72(4):276-88. doi: 10.1159/000330634. Epub 2011 Dec 23.
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.
本文介绍了软件包KELVIN,它支持用于衡量人类(或更一般地说,二倍体)遗传学研究中统计证据的PPL(连锁后验概率)框架。在范围方面,KELVIN支持基于性别平均或性别特异性遗传图谱的两点(性状-标记或标记-标记)和多点连锁分析,并可选择考虑印记;在病例对照数据、三联体数据和/或多重家系数据中进行性状-标记连锁不平衡(LD)或关联分析,可选择联合连锁以及给定连锁情况下的性状-标记LD或条件LD;二分性状、数量性状和数量性状阈值模型;以及某些类型的基因-基因相互作用和协变量效应。在分析过程中,特征和数据(系谱)结构可以自由混合和匹配。该统计框架经过专门定制,以数学上严谨的方式在多个数据集或数据子集中积累证据,同时考虑多种异质性来源,而KELVIN本身利用复杂的软件工程提供一个强大且稳健的平台,用于研究复杂疾病的遗传学。