bigscaleDE: Differential Expression

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

Performs DE over two groups of cells

Usage

bigscaleDE(object, group1, group2, speed.preset = "slow")

Arguments

object	object of the SingleCellExperiment class.
group1	a numeric vector with the indices of cells of group1
group2	a numeric vector with the indices of cells of group2
speed.preset	by default speed.preset='slow'. It regulates the speed vs. accuracy in the computation of the marker and differentially expressed genes. slow Reccomended for most datasets, provides best marker accuracy but slowest computational time. normal A balance between marker accuracy and computational time. fast Fastest computational time, if you are in a hurry and you have lots of cell (>15K) you can use this

Examples

DE=bigscale.DE(sce,group1=c(1:100),group1=c(101:200))

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