Genome-wide quantitative analysis of DNA methylation from bisulfite sequencing data

Kemal Akman, Thomas Haaf, Silvia Gravina, Jan Vijg, Achim Tresch

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

Summary: Here we present the open-source R/Bioconductor software package BEAT (BS-Seq Epimutation Analysis Toolkit). It implements all bioinformatics steps required for the quantitative high-resolution analysis of DNA methylation patterns from bisulfite sequencing data, including the detection of regional epimutation events, i.e. loss or gain of DNA methylation at CG positions relative to a reference. Using a binomial mixture model, the BEAT package aggregates methylation counts per genomic position, thereby compensating for low coverage, incomplete conversion and sequencing errors.

Original languageEnglish (US)
Pages (from-to)1933-1934
Number of pages2
JournalBioinformatics
Volume30
Issue number13
DOIs
StatePublished - Jul 1 2014

Fingerprint

DNA Methylation
Quantitative Analysis
Sequencing
Genome
Genes
Methylation
Statistical Models
Bioinformatics
Binomial Mixture
Computational Biology
Chemical analysis
Software packages
Binomial Model
Software
Mixture Model
Software Package
Open Source
Genomics
Count
Coverage

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology
  • Computational Theory and Mathematics
  • Computer Science Applications
  • Computational Mathematics
  • Statistics and Probability
  • Medicine(all)

Cite this

Genome-wide quantitative analysis of DNA methylation from bisulfite sequencing data. / Akman, Kemal; Haaf, Thomas; Gravina, Silvia; Vijg, Jan; Tresch, Achim.

In: Bioinformatics, Vol. 30, No. 13, 01.07.2014, p. 1933-1934.

Research output: Contribution to journalArticle

Akman, Kemal ; Haaf, Thomas ; Gravina, Silvia ; Vijg, Jan ; Tresch, Achim. / Genome-wide quantitative analysis of DNA methylation from bisulfite sequencing data. In: Bioinformatics. 2014 ; Vol. 30, No. 13. pp. 1933-1934.
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