/SnapATAC

Single Nucleus Analysis Package for ATAC-seq

Primary LanguageRGNU General Public License v3.0GPL-3.0

SnapATAC (Development)

SnapATAC (Single Nucleus Analysis Pipeline for ATAC-seq) is a fast and accurate method for analyzing single cell ATAC-seq datasets. SnapATAC 1) clusters cells without reliance on open chromatin peaks defined by aggregate signal; 2) adjusts for sequencing depth differing between cells; 3) can scale up to millions of cells; 4) sensitive to uncover cis-regulatory elements in rare cell types.

How fast is SnapATAC?

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.

How accurate is SnapATAC?

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.

Requirements

  • Python ( >= 2.7)
  • R (>= 3.4.0)

Installation

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 snaptools

Install SnapATAC R pakcage (development version).

$ R
> library(devtools)
> install_github("r3fang/SnapATAC")

Galleries & Tutorials (click on the image for details)