nhejazi/methyvim: Targeted, Robust, and Model-free Differential Methylation Analysis
Version 1.3.1

This package provides facilities for differential methylation analysis based on variable importance measures (VIMs), a class of statistical target parameters that arise in causal inference. The estimation and inference procedures provided are nonparametric, relying on ensemble machine learning to flexibly assess functional relationships among covariates and the outcome of interest. These tools can be applied to differential methylation at the level of CpG sites, to obtain valid statistical inference even after corrections for multiple hypothesis testing.

Getting started

Package details

AuthorNima Hejazi [aut, cre, cph], Mark van der Laan [aut, ths], Alan Hubbard [ctb, ths], Rachael Phillips [ctb]
Bioconductor views Clustering DNAMethylation DifferentialMethylation MethylSeq MethylationArray
MaintainerNima Hejazi <[email protected]>
Licensefile LICENSE
Version1.3.1
URL https://github.com/nhejazi/methyvim
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("nhejazi/methyvim")
nhejazi/methyvim documentation built on Sept. 30, 2018, 7:58 a.m.