Characterizing the targets of transcription regulators by aggregating ChIP-seq and perturbation expression data sets

TR ChIP-seq and RNA expression experiments that perturb TR activity are the most common strategies for mapping TRs to genes at a genomic scale. However, the collection, preprocessing, summarization, and integration of these data sets requires a non-trivial degree of bioinformatics experience.

In this study, we set out a framework to accomplish these tasks. We focus on eight TRs in both mouse and human, encompassing nearly 500 experiments, with two main objectives. The first is a detailed examination of the properties of the contributing experiments, to better learn of potential biases and pitfalls when aggregating diverse data sets.