run.limma.matrix: run limma, given an expression matrix

In Japrin/sscClust: simpler single cell RNAseq data clustering

run limma, given an expression matrix

Description

run limma, given an expression matrix

Usage

run.limma.matrix(
  xdata,
  xlabel,
  batch = NULL,
  out.prefix = NULL,
  ncell.downsample = NULL,
  T.fdr = 0.05,
  T.logFC = 1,
  T.expr = 0.3,
  T.bin.useZ = T,
  verbose = 0,
  n.cores = NULL,
  group = NULL,
  gid.mapping = NULL,
  do.voom = F,
  rn.seed = 9999
)

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)
ncell.downsample	integer; for each group, number of cells downsample to. (default: NULL)
T.fdr	numeric; threshold of the adjusted p value of moderated t-test (default: 0.05)
T.logFC	numeric; threshold of the absoute diff (default: 1)
T.expr	numeric; threshold for binarizing exprs (default: 0.3)
T.bin.useZ	logical; wheter use the z-score version of assay.namme for binarizing exprs (default: T)
verbose	integer; verbose (default: 0)
n.cores	integer; number of cores used, if NULL it will be determined automatically (default: NULL)
group	character; group of interest, if NULL the last group will be used (default: NULL)
gid.mapping	named character; gene id to gene symbol mapping. (default: NULL)
do.voom	logical; perform voom transfromation (default: FALSE)
rn.seed	integer; random number seed (default: 9999)

Details

diffeerentially expressed genes dectection using limma

Value

a matrix with dimention as input ( samples in rows and variables in columns)

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