README.md

In pwirapati/acdx: Aggregated Cell Differential Expression

AC⚡DX: Aggregated Cells Differential eXpression

NOTE

There is major change of interface in v1.0.1. If you'd like to keep old analysis, install by specifying the version:

devtools::install_github("pwirapati/acdx@v1.0.1")

Blurbs

This is an R package for performing aggregation of single-cell expression profiles and rank genes based on specified patterns of changes in expression across combinations of cell types and conditions.

Feature highlights:

• Aggregation of cell expression profiles based on average and standard error of the raw counts (instead of pseudo-bulk sums)
• Random-effect meta-regression with gamma-GLM-like error model, with fast implementation to be easily applied to all genes, all cell types and many bootstrap replicates
• Ranking based on flexible interest functionals that can span across cell types and conditions, allowing selecting genes based on interesing biological relationship across cell types
• Multiple-testing significance analysis based on bootstrap resampling
• Visualization of per-gene expression patterns using forest plots

Tutorial for v1.1.0

pwirapati/acdx documentation built on Jan. 11, 2021, 12:31 a.m.