Motivation: Aberrant DNA methylation in transcription factor binding sites has been shown to lead to anomalous gene regulation that is strongly associated with human disease. However, the majority of methylation-sensitive positions within transcription factor binding sites remain unknown. Here we introduce SEMplMe, a computational tool to generate predictions of the effect of methylation on transcription factor binding strength in every position within a transcription factor’s motif. Results: SEMplMe uses ChIP-seq and whole genome bisulfite sequencing to predict effects of methylation within binding sites. SEMplMe validates known methylation sensitive and insensitive positions within a binding motif, identifies cell type specific transcription factor binding driven by methylation, and outperforms SELEX-based predictions for CTCF. These predictions can be used to identify aberrant sites of DNA methylation contributing to human disease. Availability and Implementation: SEMplMe is available from https://github.com/Boyle-Lab/SEMplMe.
CITATION STYLE
Nishizaki, S. S., & Boyle, A. P. (2022). SEMplMe: a tool for integrating DNA methylation effects in transcription factor binding affinity predictions. BMC Bioinformatics, 23(1). https://doi.org/10.1186/s12859-022-04865-x
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