Obtaining PIN and Gene Sets Data

2025-02-17

Get PIN File

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"
path_to_pin_file <- get_pin_file()

You can retrieve the PIN data for the organism of your choice, by setting the org argument:

## retrieving PIN data for "Gallus_gallus"
path_to_pin_file <- get_pin_file(org = "Gallus_gallus")

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"
path_to_pin_file <- get_pin_file(path2pin = "/path/to/PIN/file")

You may also retrieve a specific version of BioGRID via setting the release argument:

## retrieving PIN data for "Mus_musculus" from BioGRID release 3.5.179
path_to_pin_file <- get_pin_file(
  org = "Mus_musculus",
  release = "3.5.179"
)

Get Gene Sets List

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

By default, get_gene_sets_list() obtains “KEGG” gene sets for “hsa”.

KEGG Pathway Gene Sets

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)
gsets_list <- get_gene_sets_list(org_code = "rno")

Reactome Pathway Gene Sets

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:

gsets_list <- get_gene_sets_list(source = "Reactome")

For Reactome, there is only one collection of pathway gene sets.

MSigDB Gene Sets

Using msigdbr, 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):

gsets_list <- get_gene_sets_list(
  source = "MSigDB",
  collection = "C2"
)

The default organism for MSigDB is “Homo sapiens”, you may obtain the gene sets data for another organism by setting the species argument:

## obtaining C5 gene sets data for "Drosophila melanogaster"
gsets_list <- get_gene_sets_list(
  source = "MSigDB",
  species = "Drosophila melanogaster",
  collection = "C5"
)
## see msigdbr::msigdbr_species() for all available organisms
msigdbr::msigdbr_species()
#> # A tibble: 20 × 2
#>    species_name                    species_common_name                          
#>    <chr>                           <chr>                                        
#>  1 Anolis carolinensis             Carolina anole, green anole                  
#>  2 Bos taurus                      bovine, cattle, cow, dairy cow, domestic cat…
#>  3 Caenorhabditis elegans          <NA>                                         
#>  4 Canis lupus familiaris          dog, dogs                                    
#>  5 Danio rerio                     leopard danio, zebra danio, zebra fish, zebr…
#>  6 Drosophila melanogaster         fruit fly                                    
#>  7 Equus caballus                  domestic horse, equine, horse                
#>  8 Felis catus                     cat, cats, domestic cat                      
#>  9 Gallus gallus                   bantam, chicken, chickens, Gallus domesticus 
#> 10 Homo sapiens                    human                                        
#> 11 Macaca mulatta                  rhesus macaque, rhesus macaques, Rhesus monk…
#> 12 Monodelphis domestica           gray short-tailed opossum                    
#> 13 Mus musculus                    house mouse, mouse                           
#> 14 Ornithorhynchus anatinus        duck-billed platypus, duckbill platypus, pla…
#> 15 Pan troglodytes                 chimpanzee                                   
#> 16 Rattus norvegicus               brown rat, Norway rat, rat, rats             
#> 17 Saccharomyces cerevisiae        baker's yeast, brewer's yeast, S. cerevisiae 
#> 18 Schizosaccharomyces pombe 972h- <NA>                                         
#> 19 Sus scrofa                      pig, pigs, swine, wild boar                  
#> 20 Xenopus tropicalis              tropical clawed frog, western clawed frog

You may also obtain the gene sets for a subcollection by setting the subcollection argument:

## obtaining C3 - MIR: microRNA targets
gsets_list <- get_gene_sets_list(
  source = "MSigDB",
  collection = "C3",
  subcollection = "MIR"
)