Skip Navigation



Bioinformatics Advance Access published online on October 25, 2008

Bioinformatics, doi:10.1093/bioinformatics/btn549
This Article
Right arrow Advance Access manuscript (PDF) Freely available
Right arrow All Versions of this Article:
24/24/2825    most recent
btn549v1
Right arrow Comments: Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when Comments are posted
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Zhang, Y.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Zhang, Y.
Social Bookmarking
 Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author (2008). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Poisson Approximation for Significance in Genome-wide ChIP-chip Tiling Arrays

Yu Zhang *

Department of Statistics, the Pennsylvania State University, 325 Thomas Bldg, State College, PA.

*To whom correspondence should be addressed. Dr. Yu Zhang, E-mail: yuzhang{at}stat.psu.edu


   Abstract

Motivation: A genome-wide ChIP-chip tiling array study requires millions of simultaneous comparisons of hybridization for significance. Controlling the false positive rate in genome-wide tiling array studies is very important, because the number of computationally identified regions can easily go beyond the capability of experimental verification. No accurate and efficient method exists for evaluating statistical significance in tiling arrays. The Bonferroni method is overly conservative and the permutation test is time consuming for genome-wide studies.

Results: Motivated by the Poisson clumping heuristic, we propose an accurate and efficient method for evaluating statistical significance in genome-wide ChIP-chip tiling arrays. The method works accurately for any large number of multiple comparisons, and the computational cost for evaluating p-values does not increase with the total number of tests. Based on a moving window approach, we demonstrate how to combine results using various window sizes to increase the detection power while maintaining a specified type I error rate. We further introduce a new FDR control that is more appropriate in measuring the false proportion of binding intervals in tiling array analysis. Our method is general and can be applied to many large-scale genomic and genetic studies.

Availability: http://www.stat.psu.edu/~yuzhang/pass.tar

Contact: yuzhang{at}stat.psu.edu

Associate Editor: Prof. Alfonso Valencia


Received on July 30, 2008; revised on October 1, 2008; accepted on October 21, 2008

Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
Nucleic Acids ResHome page
Y. Zhang, W. Wu, Y. Cheng, D. C. King, R. S. Harris, J. Taylor, F. Chiaromonte, and R. C. Hardison
Primary sequence and epigenetic determinants of in vivo occupancy of genomic DNA by GATA1
Nucleic Acids Res., September 18, 2009; (2009) gkp747v1.
[Abstract] [Full Text] [PDF]



Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.