Skip Navigation

Bioinformatics 2005 21(Suppl 1):i274-i282; doi:10.1093/bioinformatics/bti1046
This Article
Right arrow FREE Full Text (Print PDF) Freely available
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 Li, W.
Right arrow Articles by Liu, X. S.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Li, W.
Right arrow Articles by Liu, X. S.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author 2005. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions{at}oupjournals.org

A hidden Markov model for analyzing ChIP-chip experiments on genome tiling arrays and its application to p53 binding sequences

Wei Li , Clifford A. Meyer and X. Shirley Liu *

Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Harvard School of Public Health Boston, MA 02115, USA

*To whom correspondence should be addressed.

Motivation: Transcription factors (TFs) regulate gene expression by recognizing and binding to specific regulatory regions on the genome, which in higher eukaryotes can occur far away from the regulated genes. Recently, Affymetrix developed the high-density oligonucleotide arrays that tile all the non-repetitive sequences of the human genome at 35 bp resolution. This new array platform allows for the unbiased mapping of in vivo TF binding sequences (TFBSs) using Chromatin ImmunoPrecipitation followed by microarray experiments (ChIP-chip). The massive dataset generated from these experiments pose great challenges for data analysis.

Results: We developed a fast, scalable and sensitive method to extract TFBSs from ChIP-chip experiments on genome tiling arrays. Our method takes advantage of tiling array data from many experiments to normalize and model the behavior of each individual probe, and identifies TFBSs using a hidden Markov model (HMM). When applied to the data of p53 ChIP-chip experiments from an earlier study, our method discovered many new high confidence p53 targets including all the regions verified by quantitative PCR. Using a de novo motif finding algorithm MDscan, we also recovered the p53 motif from our HMM identified p53 target regions. Furthermore, we found substantial p53 motif enrichment in these regions comparing with both genomic background and the TFBSs identified earlier. Several of the newly identified p53 TFBSs are in the promoter region of known genes or associated with previously characterized p53-responsive genes.

Contact: xsliu{at}jimmy.harvard.edu

Supplementary information: Available at the following URL http://genome.dfci.harvard.edu/~xsliu/HMMTiling/index.html

Received on January 15, 2005; accepted on March 27, 2005

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
 BioinformaticsHome page
Y. Kim, S. Bekiranov, J. K. Lee, and T. Park
Double error shrinkage method for identifying protein binding sites observed by tiling arrays with limited replication
Bioinformatics, October 1, 2009; 25(19): 2486 - 2491.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
J. T. Judy and H. Ji
TileProbe: modeling tiling array probe effects using publicly available data
Bioinformatics, September 15, 2009; 25(18): 2369 - 2375.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
M. Seifert, J. Keilwagen, M. Strickert, and I. Grosse
Utilizing gene pair orientations for HMM-based analysis of promoter array ChIP-chip data
Bioinformatics, August 15, 2009; 25(16): 2118 - 2125.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
H. Choi, A. I. Nesvizhskii, D. Ghosh, and Z. S. Qin
Hierarchical hidden Markov model with application to joint analysis of ChIP-chip and ChIP-seq data
Bioinformatics, July 15, 2009; 25(14): 1715 - 1721.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
K. He, X. Li, J. Zhou, X.-W. Deng, H. Zhao, and J. Luo
NTAP: for NimbleGen tiling array ChIP-chip data analysis
Bioinformatics, July 15, 2009; 25(14): 1838 - 1840.
[Abstract] [Full Text] [PDF]

Home page
 Proc. Natl. Acad. Sci. USAHome page
A. A. Margolin, T. Palomero, P. Sumazin, A. Califano, A. A. Ferrando, and G. Stolovitzky
ChIP-on-chip significance analysis reveals large-scale binding and regulation by human transcription factor oncogenes
PNAS, January 6, 2009; 106(1): 244 - 249.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
M.-L. Martin-Magniette, T. Mary-Huard, C. Berard, and S. Robin
ChIPmix: mixture model of regressions for two-color ChIP-chip analysis
Bioinformatics, August 15, 2008; 24(16): i181 - i186.
[Abstract] [Full Text] [PDF]

Home page
 Nucleic Acids ResHome page
I. G. Lyakhov, A. Krishnamachari, and T. D. Schneider
Discovery of novel tumor suppressor p53 response elements using information theory
Nucleic Acids Res., June 1, 2008; 36(11): 3828 - 3833.
[Abstract] [Full Text] [PDF]

Home page
 Mol. Cell. Biol.Home page
P. Hatzis, L. G. van der Flier, M. A. van Driel, V. Guryev, F. Nielsen, S. Denissov, I. J. Nijman, J. Koster, E. E. Santo, W. Welboren, et al.
Genome-Wide Pattern of TCF7L2/TCF4 Chromatin Occupancy in Colorectal Cancer Cells
Mol. Cell. Biol., April 15, 2008; 28(8): 2732 - 2744.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
C. Bock and T. Lengauer
Computational epigenetics
Bioinformatics, January 1, 2008; 24(1): 1 - 10.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
H.-R. Chung, D. Kostka, and M. Vingron
A physical model for tiling array analysis
Bioinformatics, July 1, 2007; 23(13): i80 - i86.
[Abstract] [Full Text] [PDF]

Home page
 Genome ResHome page
M. B. Gerstein, C. Bruce, J. S. Rozowsky, D. Zheng, J. Du, J. O. Korbel, O. Emanuelsson, Z. D. Zhang, S. Weissman, and M. Snyder
What is a gene, post-ENCODE? History and updated definition
Genome Res., June 1, 2007; 17(6): 669 - 681.
[Abstract] [Full Text] [PDF]

Home page
 Genome ResHome page
O. Emanuelsson, U. Nagalakshmi, D. Zheng, J. S. Rozowsky, A. E. Urban, J. Du, Z. Lian, V. Stolc, S. Weissman, M. Snyder, et al.
Assessing the performance of different high-density tiling microarray strategies for mapping transcribed regions of the human genome
Genome Res., June 1, 2007; 17(6): 886 - 897.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
J. Du, J. S. Rozowsky, J. O. Korbel, Z. D. Zhang, T. E. Royce, M. H. Schultz, M. Snyder, and M. Gerstein
A supervised hidden markov model framework for efficiently segmenting tiling array data in transcriptional and chIP-chip experiments: systematically incorporating validated biological knowledge
Bioinformatics, December 15, 2006; 22(24): 3016 - 3024.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
H. Ji and W. H. Wong
TileMap: create chromosomal map of tiling array hybridizations
Bioinformatics, September 15, 2005; 21(18): 3629 - 3636.
[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.