Literature DB >> 17934315

An entropy-based measure for QTL mapping using extreme samples of population.

Yu-Mei Li1, Yang Xiang, Zhen-Qiu Sun.   

Abstract

Quantitative trait locus (QTL) mapping can be accomplished through the method of selective genotyping, which is based on the differences of frequencies between an upper sample and a lower sample in population. However, amplifying the differences in marker allele frequencies in extreme samples may increase the probability for QTL mapping. Shannon entropy, which is a nonlinear function of allele frequencies, can be used to amplify the differences in marker allele frequencies. In this paper, we present a novel measure for linkage disequilibrium (LD) between a marker and single QTL, that is based on the comparison of the entropy and conditional entropy in a marker in extreme samples of population. This measure of LD between the marker and the trait locus can be used when the marker allele frequencies are known in the extreme samples of a population. We investigate the mapping performance in both analytic and simulation scenarios of a single QTL linked to a single marker. Our results show that the measure has very reasonable performance. In addition, a simulation study is performed on the basis of the haplotype frequencies of 10 SNPs of angiotensin-I converting enzyme (ACE) genes. (c) 2007 S. Karger AG, Basel

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Year:  2007        PMID: 17934315     DOI: 10.1159/000109729

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


  4 in total

1.  An entropy test for single-locus genetic association analysis.

Authors:  Manuel Ruiz-Marín; Mariano Matilla-García; José Antonio García Cordoba; Juan Luis Susillo-González; Alejandro Romo-Astorga; Antonio González-Pérez; Agustín Ruiz; Javier Gayán
Journal:  BMC Genet       Date:  2010-03-23       Impact factor: 2.797

2.  Identifying rare variants for quantitative traits in extreme samples of population via Kullback-Leibler distance.

Authors:  Yang Xiang; Xinrong Xiang; Yumei Li
Journal:  BMC Genet       Date:  2020-11-24       Impact factor: 2.797

3.  Genetic association studies: an information content perspective.

Authors:  Cen Wu; Shaoyu Li; Yuehua Cui
Journal:  Curr Genomics       Date:  2012-11       Impact factor: 2.236

4.  Combined genotype and haplotype tests for region-based association studies.

Authors:  Sergii Zakharov; Tien Yin Wong; Tin Aung; Eranga Nishanthie Vithana; Chiea Chuen Khor; Agus Salim; Anbupalam Thalamuthu
Journal:  BMC Genomics       Date:  2013-08-21       Impact factor: 3.969

  4 in total

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