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

TLDR

The framework can be extended to other oligonucleotide microarrays and tiling array platforms. The study proposes MAT, a fast algorithm to detect transcription factor ChIP‑enriched regions on Affymetrix tiling arrays. MAT models probe behavior based on sequence and copy number, standardizes probe values, and scores regions for enrichment to compute robust p‑values and false discovery rates. MAT accurately detects ChIP regions from single or multiple samples, reduces time and cost, and is available as open‑source Python software.

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.