An introduction to computational tools for differential binding analysis with ChIP-seq data

BackgroundGene transcription in eukaryotic cells is collectively controlled by a large panel of chromatin associated proteins and ChIP-seq is now widely used to locate their binding sites along the whole genome. Inferring the differential binding sites of these proteins between biological conditions by comparing the corresponding ChIP-seq samples is of general interest, yet it is still a computationally challenging task.ResultsHere, we briefly review the computational tools developed in recent years for differential binding analysis with ChIP-seq data. The methods are extensively classified by their strategy of statistical modeling and scope of application. Finally, a decision tree is presented for choosing proper tools based on the specific dataset.ConclusionsComputational tools for differential binding analysis with ChIP-seq data vary significantly with respect to their applicability and performance. This review can serve as a practical guide for readers to select appropriate tools for their own datasets.

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