bigscale.atac: bigSCale ATAC

In zhongmicai/bigSCale2_singleCell: A framework for the analysis of single cell data (RNA-seq and ATAC-seq) including clustering,phenotyping,pseudotime and inferring gene regulatory networks.

Description

Compute cell clusters, markers and pseudotime

Usage

bigscale.atac(sce, memory.save = FALSE, fragment = 0.1)

Arguments

sce	object of the SingleCellExperiment class. The required elements are counts(sce) and rownames(sce).
memory.save	If the code fails due to memory problems switch this option on to try to overcome them.
fragment	ATAC-seq clusters are created with a recurive apporach. The clustersing stops whan the size of the smallest clusters is around fragment=0.1 (ie 10 percent) of the total cell number. If you want to partition more/less then decrease/increase the value.

Value

An sce object storing the markers, pseudotime, cluster and other results. To access the results you can use several S4 methods. Check the online quick start tutorial for more info.

Examples

sce=bigscale.atac(sce)

zhongmicai/bigSCale2_singleCell documentation built on Nov. 5, 2019, 1:26 p.m.