GroupsDiffGenes: Claculate differential gene between two type of groups.

In SaritaPoonia/unCTC: Characterising single circulating tumor cell transcriptomes

Claculate differential gene between two type of groups.

Description

Calculate the top ten most differentially elevated genes in group 1 that have a significant p-value difference. For differentiation, limma voom is utilised.

Usage

GroupsDiffGenes(
  data_mat,
  group,
  data_type = c("Normalised", "Raw"),
  Normalization_method = c("TMM", "TMMwsp", "RLE", "upperquartile", "none"),
  p_val = 0.05,
  lfc = 0,
  up_gene_number = 10
)

Arguments

data_mat	Raw or Normalized data matrix in which genes in the row and cells in columns.
group	Different groups in a vector of size equals to the sample size of data_mat
data_type	whether data is Normalised or Raw (without normalization)
Normalization_method	Only used if expresion matrix is not normalized. All normalization methods are explained in calcNormFactor function of edgeR package
p_val	Threshold p value, default is 0.05
lfc	Threshold log fold change value, default is 0
up_gene_number	select number of upregulated genes in each group

Value

Up_gene_mat return expression matrix of upregulated genes in each group

Examples

data = unCTC::Poonia_et_al._TPMData
groups = c(rep("TNBC",11),rep("NonTNBC",61))
output = GroupsDiffGenes(data_mat=data,
                          group=groups,
                          data_type="Raw",
                           Normalization_method="TMM")

SaritaPoonia/unCTC documentation built on Nov. 8, 2022, 12:07 p.m.