TY - JOUR
T1 - ChExMix
T2 - A Method for Identifying and Classifying Protein-DNA Interaction Subtypes
AU - Yamada, Naomi
AU - Kuntala, Prashant Kumar
AU - Pugh, B. Franklin
AU - Mahony, Shaun
N1 - Funding Information:
This study was supported by NIH R01 GM125722 (S.M. and B.F.P.).
Publisher Copyright:
© Copyright 2020, Mary Ann Liebert, Inc., publishers 2020.
PY - 2020/3
Y1 - 2020/3
N2 - 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.
AB - 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.
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U2 - 10.1089/cmb.2019.0466
DO - 10.1089/cmb.2019.0466
M3 - Article
C2 - 32023130
AN - SCOPUS:85081945168
SN - 1066-5277
VL - 27
SP - 429
EP - 435
JO - Journal of Computational Biology
JF - Journal of Computational Biology
IS - 3
ER -