DMRcaller

DMRcaller identifies differentially methylated regions from bisulfite sequencing data to compare methylation patterns between two conditions.


Key Features:

  • Data input: Accepts CX report files generated by Bismark from bisulfite sequencing alignments.
  • Methylation contexts: Supports analysis in both CG and non-CG contexts.
  • Output format: Reports DMRs as GRanges objects for downstream Bioconductor interoperability.
  • Integration: Implemented within the Bioconductor framework and developed in R.
  • Statistical methods: Applies rigorous statistical approaches to detect significant methylation differences between conditions.
  • Quality assurance: Employs continuous automated testing within the Bioconductor infrastructure.

Scientific Applications:

  • Epigenetic studies: Identification of differential methylation patterns underlying epigenetic regulation between conditions.
  • Gene regulation analysis: Detection of DMRs that may implicate regulatory changes affecting gene expression.
  • Biomarker discovery: Comparison of methylation differences to nominate disease-associated or condition-specific methylation biomarkers.
  • Developmental biology: Analysis of methylation dynamics across conditions relevant to development and differentiation.

Methodology:

Processes CX report files from Bismark, compares methylation patterns between two conditions to identify regions with significant methylation differences, applies statistical methods to call DMRs, and outputs results as GRanges objects while employing continuous automated testing within Bioconductor.

Topics

Collections

Details

License:
GPL-3.0
Tool Type:
command-line tool, library
Operating Systems:
Linux, Windows, Mac
Programming Languages:
R
Added:
1/17/2017
Last Updated:
11/25/2024

Operations

Data Inputs & Outputs

Publications

Huber W, Carey VJ, Gentleman R, Anders S, Carlson M, Carvalho BS, Bravo HC, Davis S, Gatto L, Girke T, Gottardo R, Hahne F, Hansen KD, Irizarry RA, Lawrence M, Love MI, MacDonald J, Obenchain V, Oleś AK, Pagès H, Reyes A, Shannon P, Smyth GK, Tenenbaum D, Waldron L, Morgan M. Orchestrating high-throughput genomic analysis with Bioconductor. Nature Methods. 2015;12(2):115-121. doi:10.1038/nmeth.3252. PMID:25633503. PMCID:PMC4509590.

Documentation

Downloads