evaluateGO_species {GOCompare} | R Documentation |
Comprehensive comparison between species using GO terms 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
evaluateGO_species(df1, df2, species1, species2, GOterm_field, test = "prop")
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") |
Value
This function will return a data.frame with the following fields:
GO | GO term analyzed |
pvalue | p-value obtained through the use of Pearson's Chi-squared Test |
FDR | Multiple comparison correction for the p-value column |
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 <- evaluateGO_species(df1= H_sapiens,
df2=A_thaliana,
species1=species1,
species2=species2,
GOterm_field=GOterm_field,
test="prop")
print(x)