Groupcomparisonlimma: Group comparison analysis using limma

In Drinchai/BloodGen3Module: This R package for performing module repertoire analyses and generating fingerprint representations

Description

The Groupcomparisonlimma function will perform group comparison analyses using "limma" function from "limma R package" and the results are expressed “at the module level” as percent of genes increased or decreased.

• Expression matrix and sample annotation files are required to perform this analysis.

• The sample annotation file must be loaded using a specific name = "sample_info".

• The names of the columns for the conditions used in the analysis must be specified.

Usage

Groupcomparisonlimma(
  data.matrix,
  sample_info = NULL,
  FC = NULL,
  pval = NULL,
  FDR = TRUE,
  Group_column = NULL,
  Test_group = "Test_group",
  Ref_group = "Control",
  SummarizedExperiment = TRUE
)

Arguments

data.matrix	Matrix of normalized expression data (not Log2 transformed).Row names are required to be valid Gene Symbols. Columns names are sample IDs or data.matrix can also be given a summarizedexperiment object and assigned data.matrix and sample_info accordingly from the object.
sample_info	A dataframe with sample annotation.
FC	Numeric value specifying the foldchange cut off that will be applied to define increase or decrease of a given transcript compared to the reference group
pval	Numeric value specifying p-value cut off or False discovery rate when FDR = TRUE
FDR	Logical operator to specify whether False discovery rate cut off (using BH-method) should be used
Group_column	Character vector identical to the column name from sample_info dataframe that specifies group annotation used for the analysis
Test_group	Character vector specifying value within the group column that will be used as Test group
Ref_group	Character vector specifying value within the group column that will be used as Reference group
SummarizedExperiment	Output data as the SummarizedExperiment class when SummarizedExperiment = TRUE

Value

         A matrix of the percentahe of module response in each group comparison

Author(s)

Darawan Rinchai [e-mail]

Examples

## data could be downloaded from ExperimentHub("GSE13015")
library(ExperimentHub)
library(SummarizedExperiment)
dat = ExperimentHub()
res = query(dat , "GSE13015")
GSE13015 = res[["EH5429"]]
Group_limma <- Groupcomparisonlimma(GSE13015, sample_info = NULL,
FC = 1.5, pval = 0.1, FDR = TRUE, Group_column = "Group_test",
Test_group = "Sepsis", Ref_group = "Control")

Drinchai/BloodGen3Module documentation built on Sept. 20, 2021, 10:31 p.m.