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The ChIP-exo Method: Identifying Protein-DNA Interactions with Near Base Pair Precision

The ChIP-exo Method: Identifying Protein-DNA Interactions with Near Base Pair Precision

Published on: December 23, 2016

Data exploration, quality control and statistical analysis of ChIP-exo/nexus experiments.

Rene Welch¹, Dongjun Chung², Jeffrey Grass^3,4

¹Department of Statistics, University of Wisconsin-Madison, Madison, WI 53706, USA.

Nucleic Acids Research

|September 16, 2017

Summary

A new R/Bioconductor package, ChIPexoQual, offers statistical quality control for ChIP-exo/nexus experiments, addressing unique challenges in analyzing transcription factor binding sites with high resolution. This tool aids in evaluating data quality and provides guidelines for effective analysis.

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Area of Science:

Genomics
Bioinformatics
Molecular Biology

Background:

ChIP-exo/nexus experiments offer high-resolution mapping of transcription factor binding sites.
These methods are modifications of the standard ChIP-seq protocol.
ChIP-exo/nexus data analysis presents unique quality control and analysis challenges compared to ChIP-seq.

Purpose of the Study:

To develop a novel statistical quality control pipeline for ChIP-exo/nexus experiments.
To create an accompanying R/Bioconductor package named ChIPexoQual.
To enable robust exploration and analysis of ChIP-exo and related high-throughput sequencing data.

Main Methods:

Development of a statistical quality control pipeline.
Implementation of the pipeline into an R/Bioconductor package, ChIPexoQual.
Evaluation of key quality control metrics including strand imbalance, library complexity, and signal enrichment using diagnostic plots and summary statistics across genomic regions with varying coverage.

Main Results:

ChIPexoQual successfully evaluates critical quality control aspects of ChIP-exo/nexus data.
The pipeline was validated using extensive public ChIP-exo/nexus datasets and new datasets from Escherichia coli.
Guidelines were established for applying QC metrics across diverse sequencing depths, offering insights into ChIP-exo data modeling.

Conclusions:

ChIPexoQual provides a valuable tool for addressing the specific QC challenges of ChIP-exo/nexus experiments.
The package facilitates the assessment of data quality, leading to more reliable transcription factor binding site mapping.
The developed guidelines enhance the interpretation and modeling of ChIP-exo data across various experimental conditions.