Linked Life Data

19584902

Source:http://linkedlifedata.com/resource/pubmed/id/19584902

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2009-12-16
pubmed:abstractText
Haplotypes can hold key information to understand the role of candidate genes in disease etiology. However, standard haplotype analysis has yet been able to fully reveal the information retained by haplotypes. In most analysis, haplotype inference focuses on relative effects compared with an arbitrarily chosen baseline haplotype. It does not depict the effect structure unless an additional inference procedure is used in a secondary post hoc analysis, and such analysis tends to be lack of power. In this study, we propose a penalized regression approach to systematically evaluate the pattern and structure of the haplotype effects. By specifying an L1 penalty on the pairwise difference of the haplotype effects, we present a model-based haplotype analysis to detect and to characterize the haplotypic association signals. The proposed method avoids the need to choose a baseline haplotype; it simultaneously carries out the effect estimation and effect comparison of all haplotypes, and outputs the haplotype group structure based on their effect size. Finally, our penalty weights are theoretically designed to balance the likelihood and the penalty term in an appropriate manner. The proposed method can be used as a tool to comprehend candidate regions identified from a genome or chromosomal scan. Simulation studies reveal the better abilities of the proposed method to identify the haplotype effect structure compared with the traditional haplotype association methods, demonstrating the informativeness and powerfulness of the proposed method.
pubmed:grant
pubmed:commentsCorrections
http://linkedlifedata.com/resource/pubmed/commentcorrection/19584902-12675692, http://linkedlifedata.com/resource/pubmed/commentcorrection/19584902-12813726, http://linkedlifedata.com/resource/pubmed/commentcorrection/19584902-12890927, http://linkedlifedata.com/resource/pubmed/commentcorrection/19584902-15481099, http://linkedlifedata.com/resource/pubmed/commentcorrection/19584902-15726584, http://linkedlifedata.com/resource/pubmed/commentcorrection/19584902-16717475, http://linkedlifedata.com/resource/pubmed/commentcorrection/19584902-16755519, http://linkedlifedata.com/resource/pubmed/commentcorrection/19584902-17118959, http://linkedlifedata.com/resource/pubmed/commentcorrection/19584902-17357076, http://linkedlifedata.com/resource/pubmed/commentcorrection/19584902-17380613, http://linkedlifedata.com/resource/pubmed/commentcorrection/19584902-18221501, http://linkedlifedata.com/resource/pubmed/commentcorrection/19584902-18252218, http://linkedlifedata.com/resource/pubmed/commentcorrection/19584902-18510652, http://linkedlifedata.com/resource/pubmed/commentcorrection/19584902-19025789
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jan
pubmed:issn
1476-5438
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
18
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
95-103
pubmed:dateRevised
2011-7-19
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
A comprehensive approach to haplotype-specific analysis by penalized likelihood.
pubmed:affiliation
Department of Statistics, North Carolina State University, Campus Box 7566, Raleigh NC 27695, USA. jytzeng@stat.ncsu.edu
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, Non-P.H.S., Research Support, N.I.H., Extramural