MASC: Mixed-effects association testing for single cells

MASC is a novel reverse single cell association strategy for testing whether a specified covariate influences the membership of single cells in any of multiple cellular subsets while accounting for technical confounds and biological variation.

Current Version

MASC 0.1.0-alpha

Requirements

MASC is written for R 3.5. It requires the following package:

• lme4

Installation

install.packages("devtools")
library(devtools)
install_github("immunogenomics/masc")

Usage

MASC expects a data frame that contains, at minimum, a factor indicating cluster membership for single cells, a factor representing the covariate of interest, and other random- and fixed-effects covariates. These latter terms should be given as character vectors that represent the name of the column with the covariate information in the input data frame.

Work in progress