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MsgbsR: An R package for analysing methylation-sensitive restriction enzyme sequencing data

  • Benjamin T. Mayne
  • , Shalem Y. Leemaqz
  • , Sam Buckberry
  • , Carlos M. Rodriguez Lopez
  • , Claire T. Roberts
  • , Tina Bianco-Miotto
  • , James Breen

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Genotyping-by-sequencing (GBS) or restriction-site associated DNA marker sequencing (RAD-seq) is a practical and cost-effective method for analysing large genomes from high diversity species. This method of sequencing, coupled with methylation-sensitive enzymes (often referred to as methylation-sensitive restriction enzyme sequencing or MRE-seq), is an effective tool to study DNA methylation in parts of the genome that are inaccessible in other sequencing techniques or are not annotated in microarray technologies. Current software tools do not fulfil all methylation-sensitive restriction sequencing assays for determining differences in DNA methylation between samples. To fill this computational need, we present msgbsR, an R package that contains tools for the analysis of methylation-sensitive restriction enzyme sequencing experiments. msgbsR can be used to identify and quantify read counts at methylated sites directly from alignment files (BAM files) and enables verification of restriction enzyme cut sites with the correct recognition sequence of the individual enzyme. In addition, msgbsR assesses DNA methylation based on read coverage, similar to RNA sequencing experiments, rather than methylation proportion and is a useful tool in analysing differential methylation on large populations. The package is fully documented and available freely online as a Bioconductor package (https://bioconductor.org/packages/release/bioc/html/msgbsR.html).

Original languageEnglish
Article number2190
JournalScientific Reports
Volume8
Issue number1
DOIs
StatePublished - Dec 1 2018

Bibliographical note

Publisher Copyright:
© 2018 The Author(s).

Funding

The authors would like to thank all the individuals who were involved in the creation of the publicly available data set (SRP004282.1) that was used as an example in this manuscript. We would also like to thank Bioconductor for their support, code reviews and development of our package. This project was funded in part by a National Health and Medical Research Council of Australia (NHMRC) Project Grant (GNT1059120) awarded to CTR and TB-M, Waite Research Institute Research Capacity Development Funding awarded to TB-M and CRL, and Cancer Council of South Australia/SAHMRI Beat Cancer Project Grant (APP1030945) awarded to TB-M. CTR is supported by a NHMRC Senior Research Fellowship GNT1020749. SB is supported by an NHMRC-ARC Dementia Research Development Fellowship Grant (APP1111206). BTM is supported by an Australian Postgraduate Award.

FundersFunder number
Cancer Council of South Australia/SAHMRI Beat Cancer ProjectAPP1030945
NHMRC-ARC
Australian National Health and Medical Research CouncilGNT1059120, APP1111206, GNT1020749

    ASJC Scopus subject areas

    • General

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