Data Exploration, Quality Control and Statistical Analysis of ChIP-exo/nexus Experiments

ChIP-exo/nexus experiments present modifications on the commonly used ChIP-seq protocol for high resolution mapping of transcription factor binding sites. Although many aspects of the ChIP-exo data analysis are similar to those of ChIP-seq, these high throughput experiments pose a number of unique quality control and analysis challenges. We develop a statistical quality control pipeline and accompanying R package, ChIPexoQual, to enable exploration and analysis of ChIP-exo and related experiments. ChIPexoQual evaluates a number of key issues including strand imbalance, library complexity, and signal enrichment of data. Assessment of these features are facilitated through diagnostic plots and summary statistics calculated over regions of the genome with varying levels of coverage. We evaluated our QC pipeline with both large collections of public ChIP-exo/nexus data and multiple, new ChIP-exo datasets from E. coli. ChIPexoQual analysis of these datasets resulted in guidelines for using these QC metrics across a wide range of sequencing depths and provided further insights for modelling ChIP-exo data. Finally, although ChIP-exo experiments have been compared to ChIP-seq experiments with single-end (SE) sequencing, we provide, for the first time, comparisons with paired-end (PE) ChIP-seq experiments. We illustrate that, at fixed sequencing depths, ChIP-exo provides higher sensitivity, specificity, and spatial resolution than PE ChIP-seq and both significantly outperform their SE ChIP-seq counterpart. Overall design: Examination of sig70 factor in E. coli: 2 growth conditions, under two treatmnent and two replicates each.