scTEP.fa: scTEP.fa

In scTEP: Single-Cell Trajectory Inference using Ensemble Pseudotimes

scTEP.fa

Description

The 'scTEP.fa' function first selects the corresponding pathway gene sets of the data set from KEGG, then intersect the genes in the expression matrix with each pathway to have an intersect gene expression matrix for all pathways.

Usage

scTEP.fa(data, genesets, data_org = "hsa", ncores = 10L, seed = NULL)

Arguments

data	A list consists of gene expression matrix.
genesets	A list consists of Homo sapiens and Mus musculus gene sets.
data_org	The organism of the data set, mmu or hsa.
ncores	Number of processor cores to use. This values is set to seed = 10L by default
seed	A parameter to set a seed for reproducibility.

Value

List with the following keys:

• faData - A large matrix consists of concatenated 2 dimensional factor analysis results of pathways.

Examples

# Load the package and the example data (goolam datas set)
library(scTEP)
#Load pathway genesets
data('genesets')
#Load example data (SCE dataset)
data("goolam")
#Get data matrix and label
expr <- as.matrix(t(SummarizedExperiment::assay(goolam)))[1:10, 1:100]

#Get data matrix and label
data = preprocessing(expr)

#Generate factor analysis results for all the intersections between data matrix and genesets
data_fa = scTEP.fa(data, genesets, ncores = 2, data_org = 'mmu', seed = 1)

scTEP documentation built on Sept. 26, 2022, 5:10 p.m.