GOCompare (version 1.0.2.2)

evaluateCAT_species: Comprehensive comparison between species using categories and Pearson's Chi-squared Tests

Description

evaluateGO_species provides a simple function to compare results of functional enrichment analysis for two species through the use of proportion tests or Pearson's Chi-squared Tests and a False discovery rate correction

Usage

evaluateCAT_species(df1, df2, species1, species2, GOterm_field, test = "prop")

Value

This function will return a data.frame with the following fields:

CAT	Category	pvalue
p-value obtained through the use of Pearson's Chi-squared Test	FDR	Multiple comparison correction for the p-value column

Arguments

df1

A data frame with the results of a functional enrichment analysis for the species 1 with an extra column "feature" with the features to be compared

df2

A data frame with the results of a functional enrichment analysis for the species 2 with an extra column "feature" with the features to be compared

species1

This is a string with the species name for the species 1 (e.g; "H. sapiens")

species2

This is a string with the species name for the species 2 (e.g; "A. thaliana")

GOterm_field

This is a string with the column name of the GO terms (e.g; "Functional_Category")

test

This is a string with the hypothesis test to be performed. Two options are provided, "prop" and "chi-squared" (default value="prop")

Examples

#Loading example datasets
data(H_sapiens)
data(A_thaliana)
#Defining the column with the GO terms to be compared
GOterm_field <- "Functional_Category"
#Defining the species names
species1 <- "H. sapiens"
species2 <- "A. thaliana"
#Running function
x <- evaluateCAT_species(df1= H_sapiens,
                       df2=A_thaliana,
                       species1=species1,
                       species2=species2,
                       GOterm_field=GOterm_field,
                         test="prop")
print(x)