Model-based analysis of tiling-arrays for ChIP-chip

doi:10.1073/pnas.0601180103

Model-based analysis of tiling-arrays for ChIP-chip

*Department of Biostatistics and Computational Biology, Dana–Farber Cancer Institute, 44 Binney Street, Boston, MA 02115;
^¶Department of Medical Oncology, Dana–Faber Cancer Institute and Harvard Medical School, 44 Binney Street, Boston, MA 02115;
^‡Department of Biostatistics, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115; and
^§Department of Statistics, University of British Columbia, 333-6356 Agricultural Road, Vancouver, BC, Canada V6T 1Z2

Edited by Michael S. Waterman, University of Southern California, Los Angeles, CA, and approved June 18, 2006
↵ ^†W.E.J., W.L., and C.A.M. contributed equally to this work. (received for review February 13, 2006)

Abstract

We propose a fast and powerful analysis algorithm, titled Model-based Analysis of Tiling-arrays (MAT), to reliably detect regions enriched by transcription factor chromatin immunoprecipitation (ChIP) on Affymetrix tiling arrays (ChIP-chip). MAT models the baseline probe behavior by considering probe sequence and copy number on each array. It standardizes the probe value through the probe model, eliminating the need for sample normalization. MAT uses an innovative function to score regions for ChIP enrichment, which allows robust P value and false discovery rate calculations. MAT can detect ChIP regions from a single ChIP sample, multiple ChIP samples, or multiple ChIP samples with controls with increasing accuracy. The single-array ChIP region detection feature minimizes the time and monetary costs for laboratories newly adopting ChIP-chip to test their protocols and antibodies and allows established ChIP-chip laboratories to identify samples with questionable quality that might contaminate their data. MAT is developed in open-source Python and is available at http://chip.dfci.harvard.edu/∼wli/MAT. The general framework presented here can be extended to other oligonucleotide microarrays and tiling array platforms.

Footnotes

^‖To whom correspondence should be sent at the * address. E-mail: xsliu{at}jimmy.harvard.edu
Author contributions: C.A.M., M.B., and X.S.L. designed research; W.E.J., W.L., and J.S.C. performed research; W.L., C.A.M., and R.G. contributed new reagents/analytic tools; W.E.J. and W.L. analyzed data; and W.E.J. and X.S.L. wrote the paper.
Conflict of interest statement: No conflicts declared.
This paper was submitted directly (Track II) to the PNAS office.
Abbreviations:

Abbreviations

ChIP-chip,

ChIP coupled with DNA microarray analysis;

chrn,

chromosome n;

ER,

estrogen receptor;

FDR,

false discovery rate;

HMM,

hidden Markov model;

MAT,

Model-based Analysis of Tiling-arrays;

PM,

perfect match;

qPCR,

quantitative PCR;

TF,

transcription factor;

3C,

ChIP triplicates;

3I,

Input triplicates;

I1–3,

Input control replicates 1–3;

C1–3,

ChIP-chip replicates 1–3.