Run Differential Expression

Usage

sce_de(
  object,
  cluster1,
  cluster2,
  resolution = 0.2,
  diffex_scheme = "louvain",
  featureType = "gene",
  tests = c("t", "wilcox", "bimod")
)

Arguments

object: a SingleCellExperiment object
cluster1: cluster 1
cluster2: cluster 2
resolution: resolution
diffex_scheme: scheme for differential expression
featureType: gene or transcript
tests: t, wilcox, or bimod

Value

a dataframe with differential expression information

Examples

data("tiny_sce")
sce_de(tiny_sce, 
colnames(tiny_sce)[1:100], 
colnames(tiny_sce)[101:200], 
diffex_scheme = "custom")
#> t
#> $t
#>            ensgene symbol        p_val avg_log2FC    p_val_adj
#> 1  ENSG00000143320 CRABP2 2.822649e-07  1.9728456 2.822649e-06
#> 2  ENSG00000127928  GNGT1 4.724220e-06 -1.9559872 2.362110e-05
#> 3  ENSG00000130561    SAG 3.558212e-05 -1.6333148 1.186071e-04
#> 4  ENSG00000281857    SAG 3.558212e-05 -1.6333148 1.186071e-04
#> 5  ENSG00000114349  GNAT1 9.276651e-05 -1.7262036 2.319163e-04
#> 6  ENSG00000139053  PDE6H 2.870684e-02  1.1588754 5.741368e-02
#> 7  ENSG00000138472 GUCA1C 1.310718e-01 -0.6823109 2.184530e-01
#> 8  ENSG00000129535    NRL 2.213987e-01 -0.4964604 2.828659e-01
#> 9  ENSG00000285493    NRL 2.213987e-01 -0.4964604 2.828659e-01
#> 10 ENSG00000170345    FOS 2.262927e-01  0.4617879 2.828659e-01
#> 11 ENSG00000120500   ARR3 6.327603e-01  0.2353529 7.030670e-01
#> 12 ENSG00000048545 GUCA1A 7.469100e-01  0.1555255 7.469100e-01
#>