CompareedgeRGLM: Creates a summary table with the number of genes under- or...

Description Usage Arguments Value Author(s) Examples

View source: R/support_functions.R

Description

Creates a summary table with the number of genes under- or overexpressed in each group and outputs several graphical representations

Usage

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CompareedgeRGLM(
  dataMat = NULL,
  annot = NULL,
  ref_group = NULL,
  groups = NULL,
  featureTab = NULL,
  norm_method = "TMMwsp"
)

Arguments

dataMat

reads matrix

annot

selected annotation of interest

ref_group

List containing one or more vectors of reference samples. Name of the vectors will be used in the results table. The length of this list should be 1 or the same length as the groups list

groups

List containing the IDs of groups to be compared with the reference samples. Names of the vectors will be used in the results table

featureTab

Feature annotations to be added to the results table

norm_method

Which method to use for normalizing ('upperquantile')

Value

A dataframe containing the foldchange and p.value of each feature

Author(s)

Eric Letouze & Celine Vallot

Examples

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data("scExp")
scExp_cf = correlation_and_hierarchical_clust_scExp(scExp)
scExp_cf = choose_cluster_scExp(scExp_cf,nclust=2,consensus=FALSE)
featureTab = as.data.frame(SummarizedExperiment::rowRanges(scExp_cf))
rownames(featureTab) = featureTab$ID
ref_group = list("C1"=scExp_cf$cell_id[which(scExp_cf$cell_cluster=="C1")])
groups = list("C2"=scExp_cf$cell_id[which(scExp_cf$cell_cluster=="C2")])
myres = CompareedgeRGLM(as.matrix(SingleCellExperiment::counts(scExp_cf)),
annot=as.data.frame(SingleCellExperiment::colData(scExp_cf)),
   ref_group=ref_group,groups=groups, featureTab=featureTab)

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