Starr: Simple Tiling Array Analysis of Affymetrix ChIP-chip data

TL;DR

Starr is an open-source R package designed to streamline the analysis of ChIP-chip data, enabling data import, quality assessment, normalization, visualization, and detection of enriched regions, facilitating comparative and integrative genomics studies.

Contribution

It introduces a comprehensive, open-source R package that simplifies and standardizes the analysis of ChIP-chip data within the Bioconductor ecosystem.

Findings

Supports data import, normalization, and visualization

Enables detection of ChIP-enriched regions

Facilitates integration with gene expression data

Abstract

Chromatin immunoprecipitation combined with DNA microarrays (ChIP-chip) is an assay for DNA-protein-binding or post-translational chromatin/histone modifications. As with all high-throughput technologies, it requires a thorough bioinformatic processing of the data for which there is no standard yet. The primary goal is the reliable identification and localization of genomic regions that bind a specific protein. The second step comprises comparison of binding profiles of functionally related proteins, or of binding profiles of the same protein in different genetic backgrounds or environmental conditions. Ultimately, one would like to gain a mechanistic understanding of the effects of DNA binding events on gene expression. We present a free, open-source R package Starr that, in combination with the package Ringo, facilitates the comparative analysis of ChIP-chip data across experiments and across different microarray platforms. Core features are data import, quality assessment, normalization and visualization of the data, and the detection of ChIP-enriched genomic regions. The use of common Bioconductor classes ensures the compatibility with other R packages. Most importantly, Starr provides methods for integration of complementary genomics data, e.g., it enables systematic investigation of the relation between gene expression and dna binding.