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biobouncer (R package)

Validate gene symbols, ontology terms, variant formats, and database accessions from R. Checks run offline against identifier patterns and pinned snapshots, or live against the source, and return the same verdict as the companion Python and JavaScript packages for the same input.

All four modes work across 50 sources. pattern and cache run offline, remote checks the live source, and existence takes the snapshot when there is one, falls back to remote, and falls back again to pattern for a source with no resolver.

Documentation is at https://www.samuelbharti.com/biobouncer/r/. The Python and JavaScript packages are documented from https://www.samuelbharti.com/biobouncer/.

Installation

Install from CRAN:

install.packages("biobouncer")

# development version from GitHub (package is in the pkg-r/ subdirectory)
pak::pak("samuelbharti/biobouncer/pkg-r")

R-universe also serves prebuilt binaries of the latest release: install.packages("biobouncer", repos = "https://samuelbharti.r-universe.dev").

Usage 

library(biobouncer)

# List what can be checked.
sources()
source_info()

# pattern mode: is the string well-formed?
check_id(c("MONDO:0005148", "mondo:5148", "GO:0006915"), source_db = "mondo")

# cache mode: does the id exist in a pinned snapshot?
check_id("MONDO:0005148", source_db = "mondo", how = "cache", version = "sample")

# Snapshot management.
biobouncer_snapshots()
biobouncer_cache_dir()
biobouncer_pull("go") # download a full snapshot into the cache directory

# Just the verdict.
is_valid_id("P04637", source_db = "uniprot")

check_id() returns a tibble with one row per input and the columns input, valid, normalized, suggestion, source_db, version, species, how, and error (the reason a remote check was left indeterminate, else NA).

Validation frameworks

Adapters wrap the core classifier so it plugs into common validation frameworks. They never reimplement any checks.

# checkmate style: check, assert, or test.
check_valid_id(c("MONDO:0005148", "mondo:5148"), "mondo")
assert_valid_id("MONDO:0005148", "mondo")
test_valid_id("MONDO:0005148", "mondo")

# shinyvalidate rule.
iv <- shinyvalidate::InputValidator$new()
iv$add_rule("term", sv_biobouncer("mondo"))

# Data-frame validation. id_predicate() returns an elementwise predicate.
is_mondo <- id_predicate("mondo")

# assertr:
df |> assertr::assert(is_mondo, term)

# validate:
rules <- validate::validator(good_terms = is_mondo(term))
validate::confront(df, rules)

Contributing

See CONTRIBUTING.md.

License

MIT. See LICENSE.