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

View ORCID ProfileSierra S. Nishizaki, View ORCID ProfileAlan P. Boyle
doi: https://doi.org/10.1101/2020.08.13.250118
Sierra S. Nishizaki
1Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA 48109
2Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA 48109
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  • ORCID record for Sierra S. Nishizaki
Alan P. Boyle
1Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA 48109
2Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA 48109
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  • For correspondence: apboyle@umich.edu
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Abstract

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.

Contact apboyle{at}umich.edu

Supplementary Information Supplementary data are available at Bioinformatics online.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted February 22, 2021.
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SEMplMe: A tool for integrating DNA methylation effects in transcription factor binding affinity predictions
Sierra S. Nishizaki, Alan P. Boyle
bioRxiv 2020.08.13.250118; doi: https://doi.org/10.1101/2020.08.13.250118
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SEMplMe: A tool for integrating DNA methylation effects in transcription factor binding affinity predictions
Sierra S. Nishizaki, Alan P. Boyle
bioRxiv 2020.08.13.250118; doi: https://doi.org/10.1101/2020.08.13.250118

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