Cell-Type-Specific Association Testing in Bulk Omics Experiments

In bulk epigenome/transcriptome experiments, molecular expression is measured in a tissue, which is a mixture of multiple types of cells. This package tests association of a disease/phenotype with a molecular marker for each cell type. The proportion of cell types in each sample needs to be given as input. The package is applicable to epigenome-wide association study (EWAS) and differential gene expression analysis. Takeuchi and Kato (submitted) "omicwas: cell-type-specific epigenome-wide and transcriptome association study".


omicwas

Cell-Type-Specific Disease Association Testing in Bulk Omics Experiments

Installation in R

In order to install the most recent version:

install.packages("devtools")
devtools::install_github("fumi-github/omicwas", build_vignettes = TRUE)

If you encounter dependency error for sva package, install it from Bioconductor:

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("sva")

To install from CRAN archive (possibly a version older than github):

install.packages("omicwas")

To uninstall package:

remove.packages("omicwas")

Usage

library(omicwas)
vignette("intro", package = "omicwas")

Information

Preprint available from bioRxiv

CSHL (14 Nov 2019) poster

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("omicwas")

0.8.0 by Fumihiko Takeuchi, 6 years ago


https://github.com/fumi-github/omicwas


Report a bug at https://github.com/fumi-github/omicwas/issues


Browse source code at https://github.com/cran/omicwas


Authors: Fumihiko Takeuchi [aut, cre]


Documentation:   PDF Manual  


GPL-3 license


Imports broom, data.table, dplyr, ff, glmnet, magrittr, MASS, matrixStats, parallel, purrr, rlang, tidyr

Suggests testthat, knitr, rmarkdown


See at CRAN