This package is for version 3.10 of Bioconductor;
for the stable, up-to-date release version, see
DMRScan.
Detection of Differentially Methylated Regions
Bioconductor version: 3.10
This package detects significant differentially methylated regions (for both qualitative and quantitative traits), using a scan statistic with underlying Poisson heuristics. The scan statistic will depend on a sequence of window sizes (# of CpGs within each window) and on a threshold for each window size. This threshold can be calculated by three different means: i) analytically using Siegmund et.al (2012) solution (preferred), ii) an important sampling as suggested by Zhang (2008), and a iii) full MCMC modeling of the data, choosing between a number of different options for modeling the dependency between each CpG.
Author: Christian M Page [aut, cre], Linda Vos [aut], Trine B Rounge [ctb, dtc], Hanne F Harbo [ths], Bettina K Andreassen [aut]
Maintainer: Christian M Page <page.ntnu at gmail.com>
Citation (from within R,
enter citation("DMRScan")
):
Installation
To install this package, start R (version
“3.6”) and enter:
if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("DMRScan")
For older versions of R, please refer to the appropriate
Bioconductor release.
Documentation
To view documentation for the version of this package installed
in your system, start R and enter:
browseVignettes("DMRScan")
Details
biocViews | Sequencing, Software, Technology, WholeGenome |
Version | 1.11.0 |
In Bioconductor since | BioC 3.5 (R-3.4) (3 years) |
License | GPL-3 |
Depends | R (>= 3.4.0) |
Imports | Matrix, MASS, RcppRoll, GenomicRanges, IRanges, GenomeInfoDb, methods, mvtnorm, stats, parallel |
LinkingTo | |
Suggests | testthat, knitr, rmarkdown |
SystemRequirements | |
Enhances | |
URL | github.com/christpa/DMRScan |
BugReports | github.com/christpa/DMRScan/issues |
Depends On Me | |
Imports Me | |
Suggests Me | |
Links To Me | |
Build Report |
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Installation instructions to use this
package in your R session.
Read more here: Source link