For retrieving the PIN file for an organism of your choice, you may use the function
get_pin_file(). As of this version, the only source for PIN data is “BioGRID”.
By default, the function downloads the PIN data from BioGRID and processes it, saves it in a temporary file and returns the path:
## the default organism is "Homo_sapiens" <- get_pin_file()path_to_pin_file
You can retrieve the PIN data for the organism of your choice, by setting the
## retrieving PIN data for "Gallus_gallus" <- get_pin_file(org = "Gallus_gallus")path_to_pin_file
You may also supply a
path/to/PIN/file to save the PIN file for later use (in this case, the path you supply will be returned):
## saving the "Homo_sapiens" PIN as "/path/to/PIN/file" <- get_pin_file(path2pin = "/path/to/PIN/file")path_to_pin_file
You may also retrieve a specific version of BioGRID via setting the
## retrieving PIN data for "Mus_musculus" from BioGRID release 3.5.179 <- get_pin_file(org = "Mus_musculus", path_to_pin_file release = "3.5.179")
To retrieve organism-specific gene sets list, you may use the function
get_gene_sets_list(). The available sources for gene sets are “KEGG”, “Reactome” and “MSigDB”. The function retrieves the gene sets data from the source and processes it into a list of two objects used by pathfindR for active-subnetwork-oriented enrichment analysis: 1. gene_sets A list containing the genes involved in each gene set 2. descriptions A named vector containing the descriptions for each gene set
get_gene_sets_list() obtains “KEGG” gene sets for “hsa”.
To obtain the gene sets list of the KEGG pathways for an organism of your choice, use the KEGG organism code for the selected organism. For a full list of all available organisms, see here.
## obtaining KEGG pathway gene sets for Rattus norvegicus (rno) <- get_gene_sets_list(org_code = "rno")gsets_list
For obtaining Reactome pathway gene sets, set the
source argument to “Reactome”. This downloads the most current Reactome pathways in gmt format and processes it into the list object that pathfindR uses:
<- get_gene_sets_list(source = "Reactome")gsets_list
For Reactome, there is only one collection of pathway gene sets.
pathfindR can retrieve all MSigDB gene sets. For this, set the
source argument to “MSigDB” and the
collection argument to the desired MSigDB collection (one of H, C1, C2, C3, C4, C5, C6, C7):
<- get_gene_sets_list(source = "MSigDB", gsets_list collection = "C2")
The default organism for MSigDB is “Homo sapiens”, you may obtain the gene sets data for another organism by setting the
## obtaining C5 gene sets data for "Drosophila melanogaster" <- get_gene_sets_list(source = "MSigDB", gsets_list species = "Drosophila melanogaster", collection = "C5")
## see msigdbr::msigdbr_show_species() for all available organisms ::msigdbr_show_species() msigdbr#> Warning: 'msigdbr::msigdbr_show_species' is deprecated. #> Use 'msigdbr_species' instead. #> See help("Deprecated") #>  "Anolis carolinensis" "Bos taurus" #>  "Caenorhabditis elegans" "Canis lupus familiaris" #>  "Danio rerio" "Drosophila melanogaster" #>  "Equus caballus" "Felis catus" #>  "Gallus gallus" "Homo sapiens" #>  "Macaca mulatta" "Monodelphis domestica" #>  "Mus musculus" "Ornithorhynchus anatinus" #>  "Pan troglodytes" "Rattus norvegicus" #>  "Saccharomyces cerevisiae" "Schizosaccharomyces pombe 972h-" #>  "Sus scrofa" "Xenopus tropicalis"
You may also obtain the gene sets for a subcollection by setting the
## obtaining C3 - MIR: microRNA targets <- get_gene_sets_list(source = "MSigDB", gsets_list collection = "C3", subcollection = "MIR")