Linked Life Data

19667080

Source:http://linkedlifedata.com/resource/pubmed/id/19667080

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
19
pubmed:dateCreated
2009-9-28
pubmed:abstractText
MOTIVATION: ChIP-chip has been widely used for various genome-wide biological investigations. Given the small number of replicates (typically two to three) per biological sample, methods of analysis that control the variance are desirable but in short supply. We propose a double error shrinkage (DES) method by using moving average statistics based on local-pooled error estimates which effectively control both heterogeneous error variances and correlation structures of an extremely large number of individual probes on tiling arrays. RESULTS: Applying DES to ChIP-chip tiling array study for discovering genome-wide protein-binding sites, we identified 8400 target regions that include highly likely TFIID binding sites. About 33% of these were well matched with the known transcription starting sites on the DBTSS library, while many other newly identified sites have a high chance to be real binding sites based on a high positive predictive value of DES. We also showed the superior performance of DES compared with other commonly used methods for detecting actual protein binding sites.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Oct
pubmed:issn
1367-4811
pubmed:author
pubmed:issnType
Electronic
pubmed:day
1
pubmed:volume
25
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
2486-91
pubmed:dateRevised
2010-10-4
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
Double error shrinkage method for identifying protein binding sites observed by tiling arrays with limited replication.
pubmed:affiliation
Department of Public Health Sciences, University of Virginia, Charlottesville, VA 22908, USA.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't, Research Support, N.I.H., Extramural