Single-Cell chromatin Accessibility and gene Expression-based Clustering. A model-based approach that is specifically designed for single-cell genomic data and can jointly cluster single-cell chromatin accessibility and single-cell gene expression data.
You can install the released version of scACE from Github:
library(devtools)
devtools::install_github("cuhklinlab/scACE")getClusterGibbs: Perform model-based clustering algorithm on single-cell genomic data using Markov Chain Monte Carlo (MCMC), jointly clustering single-cell chromatin accessibility and single-cell gene expression data.
update_all2: Perform model-based clustering algorithm on single-cell genomic data using expectation–maximization (EM) algorithm, jointly clustering sc-ATAC and sc-RNA data.
simData: Simulate single-cell genomic data by model-based approach, including single-cell chromatin accessibility and single-cell gene expression data for 2 clusters.
Please refer to the vigenette with several examples for a quick guide to scACE package.