This is the released version of DMCFB; for the devel version, see DMCFB.
Differentially Methylated Cytosines via a Bayesian Functional ApproachBioconductor version: Release (3.21)
DMCFB is a pipeline for identifying differentially methylated cytosines using a Bayesian functional regression model in bisulfite sequencing data. By using a functional regression data model, it tries to capture position-specific, group-specific and other covariates-specific methylation patterns as well as spatial correlation patterns and unknown underlying models of methylation data. It is robust and flexible with respect to the true underlying models and inclusion of any covariates, and the missing values are imputed using spatial correlation between positions and samples. A Bayesian approach is adopted for estimation and inference in the proposed method.
Author: Farhad Shokoohi [aut, cre] ORCID: 0000-0002-6224-2609
Maintainer: Farhad Shokoohi <shokoohi at icloud.com>
Citation (from within R, entercitation("DMCFB")
): Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("DMCFB")
For older versions of R, please refer to the appropriate Bioconductor release.
DocumentationTo view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("DMCFB")
Identifying DMCs using Bayesian functional regressions in BS-Seq data HTML R Script Reference Manual PDF NEWS Text Details biocViews Bayesian, Coverage, DifferentialMethylation, Regression, Sequencing, Software Version 1.22.1 In Bioconductor since BioC 3.10 (R-3.6) (5.5 years) License GPL-3 Depends R (>= 4.0.0), SummarizedExperiment, methods, S4Vectors, BiocParallel, GenomicRanges, IRanges Imports utils, stats, speedglm, MASS, data.table, splines, arm, rtracklayer, benchmarkme, tibble, matrixStats, fastDummies, graphics System Requirements URL Bug Reports https://github.com/shokoohi/DMCFB/issues See More Package Archives
Follow Installation instructions to use this package in your R session.
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