khughitt / eupathdb

EuPathDB recipe for the Bioconductor AnnotationHub

EuPathDB AnnotationHub Recipes and access

This package contains code for generating Bioconductor objects (OrgDb, OrganismDbi, TxDb, GRanges, and BSGenome) for pathogens found on one of the EuPathDB databases:

• AmoebaDB
• CryptoDB
• FungiDB
• GiardiaDB
• MicrosporidiaDB
• PiroplasmaDB
• PlasmoDB
• SchistoDB
• ToxoDB
• TrichDB
• TriTrypDB

The primary purposes for this package are:

1. Generate organism-specific Bioconductor resources to be made available through AnnotationHub.
2. Generate installable packages for the various resources.
3. Provide shortcuts for accessing these resources.

To access EuPathDB resources via AnnotationHub, simply load the AnnotationHub package and use the query function like you would for any other AnnotationHub resource:

library(AnnotationHub)

# create an AnnotationHub connection
ah <- AnnotationHub()

# use AnnotationHub to get an OrgDb object for T. gondii ME49
res <- query(ah, c('Toxoplasma gondii ME49', 'OrgDb', 'EuPathDB'))
orgdb <- res[[1]]

To create a local package of a EuPathDB resource, and get information from it:

library(EuPathDB)
## I pretty much always use Leishmania major strain friedlin as my example.
lm_entry <- get_eupath_entry(species="Friedlin")
lm_name <- sc_entry[["Species"]]
lm_name
orgdb_pkgname <- make_eupath_orgdb(lm_entry)
txdb_pkgname <- make_eupath_txdb(lm_entry)
bsgenome_pkgname <- make_eupath_bsgenome(lm_entry)
organismdbi_pkgname <- make_eupath_organismdbi(lm_entry)

## Get a big monster data table of annotations
major_annotations <- load_orgdb_annotations(orgdb_pkgname)
## Or GO categories
major_go <- load_orgdb_go(orgdb_pkgname)

avail_columns <- AnnotationDbi::columns(orgdb_pkgname)

## Or interpro categories
chosen_columns_idx <- grepl(x=avail_columns, pattern="^INTERPRO")
chosen_columns <- avail_columns[chosen_columns_idx]
lm_interpro <- load_orgdb_go(lm_orgdb, columns=chosen_columns)

## Or Orthologs
chosen_columns_idx <- grepl(x=avail_columns, pattern="^ORTHOLOGS")
chosen_columns <- avail_columns[chosen_columns_idx]
lm_ortho <- load_orgdb_go(lm_orgdb, columns=chosen_columns)

## Or Pathway data
chosen_columns_idx <- grepl(x=avail_columns, pattern="^PATHWAY")
chosen_columns <- avail_columns[chosen_columns_idx]
lm_path <- load_orgdb_go(lm_orgdb, columns=chosen_columns)

## Or KEGG
chosen_columns_idx <- grepl(x=avail_columns, pattern="KEGG")
chosen_columns <- avail_columns[chosen_columns_idx]
lm_kegg <- load_orgdb_go(lm_orgdb, columns=chosen_columns)

Check the vignettes for more examples!