findDEGenesByAOV: differential expression analysis

In Japrin/sscClust: simpler single cell RNAseq data clustering

differential expression analysis

Description

differential expression analysis

Usage

findDEGenesByAOV(
  xdata,
  xlabel,
  batch = NULL,
  out.prefix = NULL,
  pmod = NULL,
  F.FDR.THRESHOLD = 0.01,
  HSD.FDR.THRESHOLD = 0.01,
  HSD.FC.THRESHOLD = 1,
  use.Kruskal = F,
  F.only = F,
  verbose = F,
  n.cores = NULL,
  ncell.downsample = NULL,
  gid.mapping = NULL
)

Arguments

xdata	data frame or matrix; rows for genes and columns for samples
xlabel	factor; cluster label of the samples, with length equal to the number of columns in xdata
batch	factor; covariate. (default: NULL)
out.prefix	character; if not NULL, write the result to the file(s). (default: NULL)
pmod	character;
F.FDR.THRESHOLD	numeric; threshold of the adjusted p value of F-test. (default: 0.01)
HSD.FDR.THRESHOLD	numeric; threshold of the adjusted p value of HSD-test (default: 0.01)
HSD.FC.THRESHOLD	numeric; threshold of the absoute diff of HSD-test (default: 1)
use.Kruskal	logical; whether use Kruskal test for ranking genes (default: FALSE)
F.only	logical; only perform F-test (default: FALSE)
verbose	logical; whether output all genes' result. (default: F)
n.cores	integer; number of cores used, if NULL it will be determined automatically (default: NULL)
ncell.downsample	integer; for each group, number of cells downsample to. (default: NULL)
gid.mapping	named character; gene id to gene symbol mapping. (default: NULL)

Value

List with the following elements:

aov.out	data.frame, test result of all genes (rownames of xdata)
aov.out.sig	format as aov.out, but only significant genes.

Japrin/sscClust documentation built on Dec. 15, 2022, 1:04 p.m.