The data frame is the direct output of pairwise DEG test applied on example
dataset which can be loaded with importPBMC(). Cell type annotation
was obtained from SeuratData package, "ifnb" dataset, since they are the
same. Use the following command to reproduce the same result:
library(rliger)
library(Seurat)
library(SeuratData)lig <- importPBMC()
ifnb <- LoadData("ifnb")
lig$cell_type <- ifnb$seurat_annotations
lig$condition_cell_type <- interaction(lig$dataset, lig$cell_type, drop = FALSE)
deg.pw <- runPairwiseDEG(
object = lig,
groupTest = 'stim.CD14 Mono',
groupCtrl = 'ctrl.CD14 Mono',
variable1 = 'condition_cell_type'
)
deg.pw <- deg.pw[order(deg.pw$padj)[1:1000],]
```
The result represents the statistics of DEG test between stim dataset against
ctrl dataset, within the CD14 monocytes. The result is randomly sampled to
1000 entries for minimum demonstration.
[1:1000]: R:1:1000
deg.pwdata.frame object of 1000 rows with columns:
feature: gene names.
group: class name within the variable being used for the test condition.
logFC: log fold change of the gene expression between the condition of interest against the control condition.
pval: p-value of the DEG test.
padj: adjusted p-value of the DEG test.
pct_in: percentage of cells in the condition of interest expressing the gene.
pct_out: percentage of cells in the control condition expressing the gene.
runPairwiseDEG()