Single-cell sequencing assay for transposase-accessible chromatin (scATAC-seq) is the state-of-the-art technology for analyzing genome-wide regulatory landscape in single cells. Due to data sparsity and discreteness, analyzing scATAC-seq data is challenging. Existing computational methods cannot accurately reconstruct activities of individual cis-regulatory elements (CREs) in individual cells. We present a new statistical framework, SCATE, that adaptively integrates information from co-activated CREs, similar cells, and publicly available regulome data to substantially increase the accuracy for estimating individual CRE activities in single cell and rare cell subpopulations.
SCATE software can be installed via Github. Users should have R installed on their computer before installing SCATE. R version needs to be at least 3.5. R can be downloaded here: http://www.r-project.org/.
For Windows users, Rtools is also required to be installed. Rtools can be downloaded here: https://cloud.r-project.org/bin/windows/Rtools/Rtools35.exe Use default settings to perform the installation.
To install the latest version of SCATE package via Github, run following commands in R: {r } if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("GenomicAlignments,preprocessCore") if (!require("devtools")) install.packages("devtools") devtools::install_github("zji90/SCATE")
Check the following page for user manual: https://github.com/zji90/SCATE/raw/master/inst/doc/SCATE.pdf