SnapATAC (Single Nucleus Analysis Pipeline for ATAC-seq) is a fast and accurate method for analyzing single cell ATAC-seq datasets. SnapATAC 1) overcomes the limitation of reliance on population-level peak annotation, 2) improves the clustering accuracy by integrating "off-peak" reads, 3) controls for the major bias using a regression-based normalization method and 4) substantially outperforms current methods in scalability.
For 10X PBMC 10K single cell ATAC-seq dataset, from loading the cell count matrix to finding clusters, SnapATAC finishes the analysis within 4min. On average, SnapATAC increase less than 30 seconds per thousand cells.
When applied to a dataset from mouse secondary motor cortex, SnapATAC identifies nearly 50 cell types including rare population (Sst-Chodl) which accounts for less than 0.1% of the total population.
- Python ( >= 2.7)
- R (>= 3.4.0)
SnapATAC has two components: Snaptools and SnapATAC.
- SnapTools - a python module for pre-processing and working with snap file.
- SnapATAC - a R package for the clustering, annotation, motif discovery and downstream analysis.
Install snaptools from PyPI. See how to install snaptools on FAQs.
$ pip install snaptoolsInstall SnapATAC R pakcage (development version).
$ R
> library(devtools)
> install_github("r3fang/SnapATAC")
