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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

masc's People

Contributors

cfonseka avatar ilyakorsunsky avatar

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