perturbLM

A lightweight R package that uses linear models to analyze the effects of chemical/genetic perturbations, conditions, and disease states on single gene expression. Inspired by the MIMOSCA python package (https://github.com/asncd/MIMOSCA)

Install instructions

if (!require("remotes")) {
  install.packages("remotes")
}
remotes::install_github("yanwu2014/perturbLM")

Tutorials

A tutorial on how to fit an ElasticNet model on single cell perturbational response data and evaluate model performance on a per perturbation basis. This enables interpretation of perturbation effects on the transcriptome as well as other covariates (such as cell type).

Coming soon:

1. A tutorial on how to use linear models to infer non-linear interactions between perturbations
2. A tutorial on how to infer cell type specific perturbation effects