Journal Article

Double error shrinkage method for identifying protein binding sites observed by tiling arrays with limited replication

Youngchul Kim, Stefan Bekiranov, Jae K. Lee and Taesung Park

in Bioinformatics

Volume 25, issue 19, pages 2486-2491
Published in print October 2009 | ISSN: 1367-4803
Published online August 2009 | e-ISSN: 1460-2059 | DOI: http://dx.doi.org/10.1093/bioinformatics/btp471
Double error shrinkage method for identifying protein binding sites observed by tiling arrays with limited replication

More Like This

Show all results sharing this subject:

  • Bioinformatics and Computational Biology

GO

Show Summary Details

Preview

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.

Contact: tspark@snu.ac.kr; jaeklee@virginia.edu

Supplementary information: Supplementary data are available at Bioinformatics online.

Journal Article.  4598 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

Full text: subscription required

How to subscribe Recommend to my Librarian

Users without a subscription are not able to see the full content. Please, subscribe or login to access all content.