Literature DB >> 12435884

Backward Haplotype Transmission Association (BHTA) algorithm - a fast multiple-marker screening method.

Shaw-Hwa Lo1, Tian Zheng.   

Abstract

The mapping of complex traits is one of the most important and central areas of human genetics today. Recent attention has been focused on genome scans using a large number of marker loci. Because complex traits are typically caused by multiple genes, the common approaches of mapping them by testing markers one after another fail to capture the substantial information of interactions among disease loci. Here we propose a backward haplotype transmission association (BHTA) algorithm to address this problem. The algorithm can administer a screening on any disease model when case-parent trio data are available. It identifies the important subset of an original larger marker set by eliminating the markers of least significance, one at a time, after a complete evaluation of its importance. In contrast with the existing methods, three major advantages emerge from this approach. First, it can be applied flexibly to arbitrary markers, regardless of their locations. Second, it takes into account haplotype information; it is more powerful in detecting the multifactorial traits in the presence of haplotypic association. Finally, the proposed method can potentially prove to be more efficient in future genomewide scans, in terms of greater accuracy of gene detection and substantially reduced number of tests required in scans. We illustrate the performance of the algorithm with several examples, including one real data set with 31 markers for a study on the Gilles de la Tourette syndrome. Detailed theoretical justifications are also included, which explains why the algorithm is likely to select the 'correct' markers. Copyright 2002 S. Karger AG, Basel

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Year:  2002        PMID: 12435884     DOI: 10.1159/000066194

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


  12 in total

1.  A demonstration and findings of a statistical approach through reanalysis of inflammatory bowel disease data.

Authors:  Shaw-Hwa Lo; Tian Zheng
Journal:  Proc Natl Acad Sci U S A       Date:  2004-07-01       Impact factor: 11.205

2.  Logic Forest: an ensemble classifier for discovering logical combinations of binary markers.

Authors:  Bethany J Wolf; Elizabeth G Hill; Elizabeth H Slate
Journal:  Bioinformatics       Date:  2010-07-13       Impact factor: 6.937

3.  Multilocus linkage analysis of affected sib pairs.

Authors:  Iuliana Ionita; Shaw-Hwa Lo
Journal:  Hum Hered       Date:  2006-01-17       Impact factor: 0.444

4.  Backward genotype-trait association (BGTA)-based dissection of complex traits in case-control designs.

Authors:  Tian Zheng; Hui Wang; Shaw-Hwa Lo
Journal:  Hum Hered       Date:  2006-11-15       Impact factor: 0.444

5.  Interaction-based feature selection and classification for high-dimensional biological data.

Authors:  Haitian Wang; Shaw-Hwa Lo; Tian Zheng; Inchi Hu
Journal:  Bioinformatics       Date:  2012-09-03       Impact factor: 6.937

6.  The challenge of detecting epistasis (G x G interactions): Genetic Analysis Workshop 16.

Authors:  Ping An; Odity Mukherjee; Pritam Chanda; Li Yao; Corinne D Engelman; Chien-Hsun Huang; Tian Zheng; Ilija P Kovac; Marie-Pierre Dubé; Xueying Liang; Jia Li; Mariza de Andrade; Robert Culverhouse; Doerthe Malzahn; Alisa K Manning; Geraldine M Clarke; Jeesun Jung; Michael A Province
Journal:  Genet Epidemiol       Date:  2009       Impact factor: 2.135

7.  Discovering interactions among BRCA1 and other candidate genes associated with sporadic breast cancer.

Authors:  Shaw-Hwa Lo; Herman Chernoff; Lei Cong; Yuejing Ding; Tian Zheng
Journal:  Proc Natl Acad Sci U S A       Date:  2008-08-18       Impact factor: 11.205

8.  Whole-genome association studies on alcoholism comparing different phenotypes using single-nucleotide polymorphisms and microsatellites.

Authors:  Liang Chen; Nianjun Liu; Shuang Wang; Cheongeun Oh; Nicholas J Carriero; Hongyu Zhao
Journal:  BMC Genet       Date:  2005-12-30       Impact factor: 2.797

9.  Rheumatoid arthritis-associated gene-gene interaction network for rheumatoid arthritis candidate genes.

Authors:  Chien-Hsun Huang; Lei Cong; Jun Xie; Bo Qiao; Shaw-Hwa Lo; Tian Zheng
Journal:  BMC Proc       Date:  2009-12-15

10.  Selecting informative genes for discriminant analysis using multigene expression profiles.

Authors:  Xin Yan; Tian Zheng
Journal:  BMC Genomics       Date:  2008-09-16       Impact factor: 3.969

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