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Modbamtools: Analysis of single-molecule epigenetic data for long-range profiling, heterogeneity, and clustering

View ORCID ProfileRoham Razaghi, View ORCID ProfilePaul W. Hook, View ORCID ProfileShujun Ou, View ORCID ProfileMichael C. Schatz, View ORCID ProfileKasper D. Hansen, View ORCID ProfileMiten Jain, View ORCID ProfileWinston Timp
doi: https://doi.org/10.1101/2022.07.07.499188
Roham Razaghi
1Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA
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Paul W. Hook
1Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA
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Shujun Ou
2Department of Biology and Computer Science, Johns Hopkins University, Baltimore, Maryland, USA
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Michael C. Schatz
2Department of Biology and Computer Science, Johns Hopkins University, Baltimore, Maryland, USA
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Kasper D. Hansen
3Department of Biostatistics, Johns Hopkins School of Public Health, Baltimore, MD, USA
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Miten Jain
4Department of Bioengineering, Department of Physics, Northeastern University, Boston, MA
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Winston Timp
1Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA
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  • For correspondence: wtimp@jhu.edu
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Abstract

The advent of long-read sequencing methods provides new opportunities for profiling the epigenome - especially as the methylation signature comes for “free” when native DNA is sequenced on either Oxford Nanopore or Pacific Biosciences instruments. However, we lack tools to visualize and analyze data generated from these new sources. Recent efforts from the GA4GH consortium have standardized methods to encode modification location and probabilities in the BAM format. Leveraging this standard format, we developed a technology-agnostic tool, modbamtools to visualize, manipulate and compare base modification/methylation data in a fast and robust way. modbamtools can produce high quality, interactive, and publication-ready visualizations as well as provide modules for downstream analysis of base modifications. Modbamtools comprehensive manual and tutorial can be found at https://rrazaghi.github.io/modbamtools/.

Competing Interest Statement

W.T. has two patents (8,748,091 and 8,394,584) licensed to ONT.

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 4.0 International license.
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Posted July 08, 2022.
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Modbamtools: Analysis of single-molecule epigenetic data for long-range profiling, heterogeneity, and clustering
Roham Razaghi, Paul W. Hook, Shujun Ou, Michael C. Schatz, Kasper D. Hansen, Miten Jain, Winston Timp
bioRxiv 2022.07.07.499188; doi: https://doi.org/10.1101/2022.07.07.499188
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Modbamtools: Analysis of single-molecule epigenetic data for long-range profiling, heterogeneity, and clustering
Roham Razaghi, Paul W. Hook, Shujun Ou, Michael C. Schatz, Kasper D. Hansen, Miten Jain, Winston Timp
bioRxiv 2022.07.07.499188; doi: https://doi.org/10.1101/2022.07.07.499188

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