A Tidyverse-Native Client for the BrAPI v2 (Breeding API) Specification • brapiR2

brapiR2 is a tidyverse-native, stateless R client for the BrAPI v2 (Breeding API) specification. It provides pipe-friendly access to all four BrAPI modules - Core, Germplasm, Phenotyping, and Genotyping - returning tidy tibbles ready for analysis.

Developed by Joash Joshua Ayo (joashjoshua789@gmail.com).

Why brapiR2?

Feature	brapiR2	QBMS
Design	Stateless, functional, pipeable	Stateful, menu-driven
BrAPI v2 coverage	Full spec (all 4 modules)	Partial (phenotyping focus)
Genotyping support	Native variants, callsets, dosage matrix	Via GIGWA wrapper
Return type	Always tibbles	Mixed lists/dataframes
Auth	Unified token/OAuth2	Engine-specific functions
Caching	Built-in response caching	Limited

brapiR2 complements QBMS - use QBMS for interactive exploration, use brapiR2 for programmatic pipelines and custom tooling.

Installation

Install the development version from GitHub:

# install.packages("remotes")
remotes::install_github("josh45-source/brapiR2")

Quick Start

library(brapiR2)
library(dplyr)

# 1. Connect (no global state!)
con <- brapi_connection("https://test-server.brapi.org")

# 2. Explore programs and trials
brapi_programs(con)

brapi_trials(con) |>
  filter(active == TRUE) |>
  head()

# 3. Get phenotypic data in analysis-ready wide format
data <- brapi_study_data(con, "study_01")

# 4. Get genotypic data as a dosage matrix for GS
dosage <- brapi_get_dosage_matrix(con, "variantset_01")

# 5. Parallel fetch across multiple studies
all_data <- brapi_fetch_parallel(
  con,
  brapi_study_data,
  ids = c("study_01", "study_02", "study_03"),
  .workers = 4
)

Pipe-Friendly Design

Every function takes a connection object as its first argument and returns a tibble, making it natural to chain with dplyr:

con <- brapi_connection("https://my-breedbase.org", token = "my_token")

# Find all germplasm used in a specific study
brapi_observation_units(con, studyDbId = "study_42") |>
  select(germplasmDbId, germplasmName) |>
  distinct()

# Get marker positions for a genotyping dataset
brapi_get_marker_map(con, "my_variantset") |>
  filter(referenceName == "chr1") |>
  arrange(start)

Supported BrAPI Modules

Core: Programs, Trials, Studies, Locations, Seasons, Lists, People
Germplasm: Germplasm, Pedigrees, Progeny, Attributes, Crosses, Seed Lots
Phenotyping: Observation Units, Observations, Variables, Traits, Scales, Methods, Images, Events
Genotyping: Samples, Variants, Variant Sets, Calls, Call Sets, References, Allele Matrix

Authentication

# Token-based (most BrAPI servers)
con <- brapi_connection("https://my-breedbase.org")
con <- brapi_login(con, "username", "password")

# OAuth 2.0 (EBS and similar)
con <- brapi_login_oauth2(
  con,
  client_id = "my_id",
  client_secret = "my_secret",
  authorize_url = "https://auth.example.org/authorize",
  access_url = "https://auth.example.org/token"
)

# Or set an existing token directly
con <- brapi_set_token(con, "my_existing_token")

QBMS — High-level, stateful BrAPI client for interactive use
rrBLUP — Genomic selection (use brapiR2 to fetch the dosage matrix)
sommer — Mixed models for multi-environment trials

Contributing

Contributions are welcome! Please see CONTRIBUTING.md for guidelines.

brapiR2