GSVA_difference: This function is used to perform GSVA analysis between two...

In Lian-Lab/LIANLAB: To integrate analysis methods and simplify analysis process

Description

This function is used to perform GSVA analysis between two clusters

Usage

GSVA_difference(
  em = NULL,
  seurat_object = NULL,
  gspath = NULL,
  species = "mouse",
  group = NULL,
  adjPvalueCutoff = 0.001,
  logFCcutoff = 0.1,
  text.size = 2,
  topn = 20,
  min.sz = 2,
  width = 6,
  height = 5,
  filename = NULL,
  ylimit = 10
)

Arguments

em	expression matrix as genes in row, samples or cells in column
seurat_object	it also support a seurat_object instead of expression matrix
gspath	the correct path of your geneset file(.gmt)
species	"mouse"(default),'human'
group	a vector of two group,if em is a expression data,it need supply
adjPvalueCutoff	cutof the P.adjust
logFCcutoff	cutoff the logFC
text.size	the size of the text
topn	number of the top pathways
min.sz	minimum size of the resulting gene sets
width	the width of the figure
height	the height of the figure
filename	the name of the generated file
ylimit	limit of the y aes

Value

seurat.obj with the score of the pathways

Examples

## Not run: 
input.file <- system.file('extdata','pbmc_1k.RDS',package = 'LIANLABDATA')
pbmc_1k <- readRDS(input.file)
GSVA_pheatmap( pbmc_1k,species="mouse",group=c('1','2'))

## End(Not run)

Lian-Lab/LIANLAB documentation built on June 23, 2021, 5:37 a.m.