Linked Life Data

19209716

Source:http://linkedlifedata.com/resource/pubmed/id/19209716

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2009-2-12
pubmed:abstractText
Several influential studies of genotypic determinants of gene expression in humans have now been published based on various populations including HapMap cohorts. The magnitude of the analytic task (transcriptome vs. SNP-genome) is a hindrance to dissemination of efficient, thorough, and auditable inference methods for this project. We describe the structure and use of Bioconductor facilities for inference in genetics of gene expression, with simultaneous application to multiple HapMap cohorts. Tools distributed for this purpose are readily adapted for the structure and analysis of privately-generated data in expression genetics.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:issn
1793-5091
pubmed:author
pubmed:issnType
Print
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
380-90
pubmed:dateRevised
2011-11-17
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
Interpreting genetics of gene expression: integrative architecture in Bioconductor.
pubmed:affiliation
Channing Laboratory, Brigham and Women's Hospital, Harvard Medical School, 181 Longwood Ave., Boston, MA 02115, USA. stvjc@channing.harvard.edu
pubmed:publicationType
Journal Article, Research Support, N.I.H., Extramural