View source: R/compareGOspecies.R
compareGOspecies | R Documentation |
compareGOspecies function provides a simple workflow to compare results of functional enrichment analysis for two species.
To use this function you will need two matrices with a column which, represents the features to be compared (e.g.feature). This function will extract the unique GO terms for two matrices and it will generate a presence-absence matrix where rows will represent a combination of categories and species (e.g H.sapiens AID) and columns will represent the GO terms analyzed. Further, this function will calculate Jaccard distances and it will provide as outputs a list with four slots: 1.) A principal coordinates analysis (PCoA) 2.) The Jaccard distance matrix 3.) A list of shared GO terms between species 4.) Finally, a list of the unique GO terms and the belonging to the respective species.
compareGOspecies( df1, df2, GOterm_field, species1, species2, skipPCoA = FALSE, paired_lists = TRUE )
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 |
GOterm_field |
This is a string with the column name of the GO terms (e.g; "Functional_Category") |
species1 |
This is a string with the species name for species 1 (e.g; "H. sapiens") |
species2 |
This is a string with the species name for species 2 (e.g; "A. thaliana") |
skipPCoA |
This is a boolean to indicate if the PCoA graphics can be skipped |
paired_lists |
This is a boolean to indicate if both species have same comparable categories (gene lists). If the paired_lists is FALSE the counts will be done only for species and categories will be kept in the outcomes. Please use carefully when paired_lists = FALSE. |
This function will return a list with four slots: graphics, distance shared_GO_list, and unique_GO_list
Do not use "-" in the feature column. This will lead to wrong results!
#Loading example datasets data(H_sapiens_compress) data(A_thaliana_compress) #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 <- compareGOspecies(df1=H_sapiens_compress, df2=A_thaliana_compress, GOterm_field=GOterm_field, species1=species1, species2=species2, skipPCoA=FALSE, paired_lists=TRUE) ## Not run: #Displaying PCoA results x$graphics # Checking shared GO terms between species print(tapply(x$shared_GO_list$feature,x$shared_GO_list$feature,length)) ## End(Not run)
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