Literature DB >> 15192281

A new method for computing the multipoint posterior probability of linkage.

Mark W Logue1, Veronica J Vieland.   

Abstract

The posterior probability of linkage (PPL) is a Bayesian statistic which directly measures the probability of linkage between a trait locus and a marker (in the 2-point case) or a genomic region (in the multipoint case). It has several benefits, including ease of interpretation, the ability to incorporate prior genomic information, and a mathematically rigorous and robust procedure for accumulating linkage information across multiple heterogeneous datasets. To date, the majority of work on the PPL has focused on the development of the 2-point statistic, with only preliminary attempts at the development of an equivalent multipoint version. In this paper we present a new way of computing of the multipoint PPL. This new version imputes to each genomic point an estimate of the 2-point PPL we would have obtained from a fully informative marker giving similar evidence for linkage. This version, which we call the imputed PPL, is shown to be superior to previously developed versions. Copyright 2004 S. Karger AG, Basel

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Year:  2004        PMID: 15192281     DOI: 10.1159/000077546

Source DB:  PubMed          Journal:  Hum Hered        ISSN: 0001-5652            Impact factor:   0.444


  11 in total

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7.  Posterior probability of linkage analysis of autism dataset identifies linkage to chromosome 16.

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8.  KELVIN: a software package for rigorous measurement of statistical evidence in human genetics.

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Journal:  Hum Hered       Date:  2011-12-23       Impact factor: 0.444

9.  Two novel quantitative trait linkage analysis statistics based on the posterior probability of linkage: application to the COGA families.

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Journal:  BMC Genet       Date:  2005-12-30       Impact factor: 2.797

10.  Performance comparison of two-point linkage methods using microsatellite markers flanking known disease locations.

Authors:  Mark W Logue; Andrew W George; M Anne Spence; Veronica J Vieland
Journal:  BMC Genet       Date:  2005-12-30       Impact factor: 2.797

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