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Comparative co-localization analysis of transcription factors (TFs) and epigenetic marks (EMs) in specific biological contexts is one of the most critical areas of ChIP-Seq data analysis beyond peak calling. Yet there is a significant lack of user-friendly and powerful tools geared towards co-localization analysis based exploratory research. Most tools currently used for co-localization analysis are command line only and require extensive installation procedures and Linux expertise. Online tools partially address the usability issues of command line tools, but slow response times and few customization features make them unsuitable for rapid data-driven interactive exploratory research. We have developed PAPST: Peak Assignment and Profile Search Tool, a user-friendly yet powerful platform with a unique design, which integrates both gene-centric and peak-centric co-localization analysis into a single package. Most of PAPST’s functions can be completed in less than five seconds, allowing quick cycles of data-driven hypothesis generation and testing. With PAPST, a researcher with or without computational expertise can perform sophisticated co-localization pattern analysis of multiple TFs and EMs, either against all known genes or a set of genomic regions obtained from public repositories or prior analysis. PAPST is a versatile, efficient, and customizable tool for genome-wide data-driven exploratory research. Creatively used, PAPST can be quickly applied to any genomic data analysis that involves a comparison of two or more sets of genomic coordinate intervals, making it a powerful tool for a wide range of exploratory genomic research. We first present PAPST’s general purpose features then apply it to several public ChIP-Seq data sets to demonstrate its rapid execution and potential for cutting-edge research with a case study in enhancer analysis. To our knowledge, PAPST is the first software of its kind to provide efficient and sophisticated post peak-calling ChIP-Seq data analysis as an easy-to-use interactive application. PAPST is available at and is a public domain work.


This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication

Data Availability: "Software and test data can be downloaded at"

Funding: This work was supported by the Intramural Research Program and the Office of Science and Technology of the National Institute of Arthritis and Musculoskeletal and Skin Diseases of the National Institutes of Health.