View source: R/evaluateGO_species.R
evaluateGO_species | R Documentation |
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
evaluateGO_species(df1, df2, species1, species2, GOterm_field, test = "prop")
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") |
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 |
#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)
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