This directory holds the R package for biobouncer. See the repository
root README.md for what biobouncer does and
PLAN.md for the architecture.
Offline pattern and cache modes, live
remote mode, and existence mode (snapshot
first, then remote) work across 46 sources.
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).
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)From the repository root:
# generate NAMESPACE and man pages
roxygen2::roxygenise("pkg-r")
# run the tests
testthat::test_dir("pkg-r/tests/testthat")Shared source definitions and the conformance corpus live in
shared/ at the repository root and are vendored into
inst/extdata/ by python tools/sync_shared.py.
Do not edit the vendored copies by hand.