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

Authors :
Alan P. Boyle
Sierra S. Nishizaki
Publication Year :
2022
Publisher :
My University, 2022.

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 factor’s 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 fromhttps://github.com/Boyle-Lab/SEMplMe.Contactapboyle@umich.eduSupplementary InformationSupplementary data are available atBioinformaticsonline.

Details

Language :
English
Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....d23866f3c15c8a9bfbef825d3fb234c8
Full Text :
https://doi.org/10.7302/4897