Rapid innovation in ChIP-seq peak-calling algorithms is outdistancing benchmarking efforts.

The current understanding of the regulation of transcription does not keep the pace with the spectacular advances in the determination of genomic sequences. Chromatin immunoprecipitation followed by massively parallel sequencing (ChIP-seq) promises to give better insight into transcription regulation by locating sites of protein-DNA interactions. Such loci of putative interactions can be inferred from the genome-wide distributions of ChIP-seq data by peak-calling software. The analysis of ChIP-seq data critically depends on this step and a multitude of these peak-callers have been deployed in the recent years. A recent study reported severe variation among peak-calling results. Yet, peak-calling still lacks systematic quantitative benchmarking. Here, we summarize benchmarking efforts and explain potential drawbacks of each benchmarking method.