Linked Life Data

17701906

Source:http://linkedlifedata.com/resource/pubmed/id/17701906

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
2007-8-16
pubmed:abstractText
For genomewide association (GWA) studies in family-based designs, we propose a novel two-stage strategy that weighs the association P values with the use of independently estimated weights. The association information contained in the family sample is partitioned into two orthogonal components--namely, the between-family information and the within-family information. The between-family component is used in the first (i.e., screening) stage to obtain a relative ranking of all the markers. The within-family component is used in the second (i.e., testing) stage in the framework of the standard family-based association test, and the resulting P values are weighted using the estimated marker ranking from the screening step. The approach is appealing, in that it ensures that all the markers are tested in the testing step and, at the same time, also uses information from the screening step. Through simulation studies, we show that testing all the markers is more powerful than testing only the most promising ones from the screening step, which was the method suggested by Van Steen et al. A comparison with a population-based approach shows that the approach achieves comparable power. In the presence of a reasonable level of population stratification, our approach is only slightly affected in terms of power and, since it is a family-based method, is completely robust to spurious effects. An application to a 100K scan in the Framingham Heart Study illustrates the practical advantages of our approach. The proposed method is of general applicability; it extends to any setting in which prior, independent ranking of hypotheses is available.
pubmed:grant
pubmed:commentsCorrections
http://linkedlifedata.com/resource/pubmed/commentcorrection/17701906-11315092, http://linkedlifedata.com/resource/pubmed/commentcorrection/17701906-11855957, http://linkedlifedata.com/resource/pubmed/commentcorrection/17701906-12214309, http://linkedlifedata.com/resource/pubmed/commentcorrection/17701906-14502464, http://linkedlifedata.com/resource/pubmed/commentcorrection/17701906-15761122, http://linkedlifedata.com/resource/pubmed/commentcorrection/17701906-15937480, http://linkedlifedata.com/resource/pubmed/commentcorrection/17701906-16400608, http://linkedlifedata.com/resource/pubmed/commentcorrection/17701906-16614226, http://linkedlifedata.com/resource/pubmed/commentcorrection/17701906-16646795, http://linkedlifedata.com/resource/pubmed/commentcorrection/17701906-16648850, http://linkedlifedata.com/resource/pubmed/commentcorrection/17701906-16862161, http://linkedlifedata.com/resource/pubmed/commentcorrection/17701906-17068223, http://linkedlifedata.com/resource/pubmed/commentcorrection/17701906-17293876, http://linkedlifedata.com/resource/pubmed/commentcorrection/17701906-17436246, http://linkedlifedata.com/resource/pubmed/commentcorrection/17701906-18319080, http://linkedlifedata.com/resource/pubmed/commentcorrection/17701906-7607457
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Sep
pubmed:issn
0002-9297
pubmed:author
pubmed:issnType
Print
pubmed:volume
81
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
607-14
pubmed:dateRevised
2010-11-18
pubmed:meshHeading
pubmed:year
2007
pubmed:articleTitle
Genomewide weighted hypothesis testing in family-based association studies, with an application to a 100K scan.
pubmed:affiliation
Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA. iionita@hsph.harvard.edu
pubmed:publicationType
Journal Article, Research Support, N.I.H., Extramural