Linked Life Data

10861894

Source:http://linkedlifedata.com/resource/pubmed/id/10861894

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2000-8-30
pubmed:abstractText
Advances in marker technology have made a dense marker map a reality. If each marker is considered separately, and separate tests for association with a disease gene are performed, then multiple testing becomes an issue. A common solution uses a Bonferroni correction to account for multiple tests performed. However, with dense marker maps, neighboring markers are tightly linked and may have associated alleles; thus tests at nearby marker loci may not be independent. When alleles at different marker loci are associated, the Bonferroni correction may lead to a conservative test, and hence a power loss. As an alternative, for tests of association that use family data, we propose a Monte Carlo procedure that provides a global assessment of significance. We examine the case of tightly linked markers with varying amounts of association between them. Using computer simulations, we study a family-based test for association (the transmission/disequilibrium test), and compare its power when either the Bonferroni or Monte Carlo procedure is used to determine significance. Our results show that when the alleles at different marker loci are not associated, using either procedure results in tests with similar power. However, when alleles at linked markers are associated, the test using the Monte Carlo procedure is more powerful than the test using the Bonferroni procedure. This proposed Monte Carlo procedure can be applied whenever it is suspected that markers examined have high amounts of association, or as a general approach to ensure appropriate significance levels and optimal power.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Jul
pubmed:issn
0741-0395
pubmed:author
pubmed:copyrightInfo
Copyright 2000 Wiley-Liss, Inc.
pubmed:issnType
Print
pubmed:volume
19
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
18-29
pubmed:dateRevised
2010-11-18
pubmed:meshHeading
pubmed:year
2000
pubmed:articleTitle
Circumventing multiple testing: a multilocus Monte Carlo approach to testing for association.
pubmed:affiliation
Institute for Clinical and Epidemiological Research, Veterans Affairs Medical Center, Durham, North Carolina, USA.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S., Research Support, U.S. Gov't, Non-P.H.S., Research Support, Non-U.S. Gov't