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bioRxiv · 10.1101/2020.08.13.250118

SEMplMe: A tool for integrating DNA methylation effects in transcription factor binding affinity predictions

Nishizaki, S. S.·Boyle, A. P.
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Abstract

MotivationAberrant 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 factors motif. ResultsSEMplMe 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 ImplementationSEMplMe is available from https://github.com/Boyle-Lab/SEMplMe. Contactapboyle@umich.edu Supplementary InformationSupplementary data are available at Bioinformatics online.

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Nishizaki, S. S., Boyle, A. P.. 2020-08-14. SEMplMe: A tool for integrating DNA methylation effects in transcription factor binding affinity predictions. https://doi.org/10.1101/2020.08.13.250118

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