setODgenes: setODgenes

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

Computes the numerical model at the core of all bigSCale2 analysis.

Usage

setODgenes(object, min_ODscore = 2.33, use.exp = c(0, 1),
  custom.genes = NA)

Arguments

min_ODscore	the treshold (Z-score) used to select highly variable genes. Increasing(decreasing) it results in less(more) highly variable genes.
use.exp	A vactor of two elements c(a,b): lower and upper quantile of expression for restricting the selection of highly variable genes. Only the genes whose expression quantile is higher than c(a) and lower than c(b) will be used for highyl variable genes. For example, if your clustering is driven by lots of highly expressed genes (Ribosomal, Mitochondrial, ..) you can set something like use.exp=c(0,0.9) to discard them.
custom.genes	A character vector with a custo set of highly variable genes. Overrides any of the previous arguments
sce	object of the SingleCellExperiment class.

Value

object of the SingleCellExperiment class, with the highly variable genes stored inside.

Examples

sce=setODgenes(sce)
sce=setODgenes(sce,min_ODscore=2) # I want to use more highly variable geness so I lower the threshold.

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