ChExMix: A Method for Identifying and Classifying Protein-DNA Interaction Subtypes

Naomi Yamada, Prashant Kumar Kuntala, B. Franklin Pugh, Shaun Mahony

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Regulatory proteins can employ multiple direct and indirect modes of interaction with the genome. The ChIP-exo mixture model (ChExMix) provides a principled approach to detecting multiple protein-DNA interaction modes in a single ChIP-exo experiment. ChExMix discovers and characterizes binding event subtypes in ChIP-exo data by leveraging both protein-DNA cross-linking signatures and DNA motifs. In this study, we present a summary of the major features and applications of ChExMix. We demonstrate that ChExMix does not require high-resolution protein-DNA binding assay data to detect binding event subtypes. Specifically, we apply ChExMix to analyze 393 ChIP-seq data profiles in K562 cells. Similar binding event subtypes are discovered across multiple proteins, suggesting the existence of colocalized regulatory protein modules that are recruited to DNA through a particular sequence-specific transcription factor. Our results thus suggest that ChExMix can characterize protein-DNA binding interaction modes using data from multiple types of protein-DNA interaction assays.

Original languageEnglish (US)
Pages (from-to)429-435
Number of pages7
JournalJournal of Computational Biology
Issue number3
StatePublished - Mar 2020

All Science Journal Classification (ASJC) codes

  • Modeling and Simulation
  • Molecular Biology
  • Genetics
  • Computational Mathematics
  • Computational Theory and Mathematics


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