BKBreed

Colourful Biometrical Analysis for Plant Breeding and Genetics

BKBreed is a small, accurate R package that runs the everyday analyses of a plant-breeding programme in one call each — and returns a publication-ready, stunningly colourful ggplot2 figure for every result through a single verb: bk_plot().

It was built to be different from the existing agricultural-statistics packages (e.g. agricolae, AgroR, metan, aridagri): those are broad and console-first; BKBreed is genetics-focused, figure-first, and covers the augmented (unreplicated) designs that balanced-only packages cannot.

What it does

Domain Function Signature figure
Randomised Block Design bk_rbd() ranked genotype means + CD letters
Factorial RBD bk_frbd() interaction line plot
Augmented Alpha-Lattice / RCBD bk_augmented() adjusted-means lollipop vs check line
Genetic variability (GCV, PCV, h², GA) bk_variability() GCV vs PCV bars + heritability
Genotypic & phenotypic correlation bk_correlation() diverging correlation heatmap
Path-coefficient analysis bk_path() direct/indirect effect matrix
Line × Tester combining ability bk_lxt() GCA effect bars + SCA heatmap
Griffing diallel (Method 2, Model I) bk_diallel() GCA effect bars + SCA heatmap
Mahalanobis D² divergence bk_diversity() D² principal-coordinate clusters
G×E stability (Eberhart-Russell + AMMI) bk_stability() AMMI-2 biplot & E-R plot

Every function also returns a tidy result object with a formatted print() method (ANOVA tables with SS/MS/F/p, SE, CD, CV%, letter groupings).

Install

From the package folder (source):

# option A — install the built tarball
install.packages("BKBreed_0.1.0.tar.gz", repos = NULL, type = "source")

# option B — install directly from GitHub
# remotes::install_github("bkpraveenars-del/BKBreed")

Dependencies: ggplot2 (required); ggrepel, patchwork (optional, for nicer labels). R ≥ 4.0.

60-second tour

library(BKBreed)

## 1. RBD — one call gives ANOVA + CD + letters + a colour figure
rbd <- bk_rbd(bk_data("rbd"), trait = "grain_yield",
              gen = "genotype", rep = "rep")
rbd            # formatted ANOVA + ranked means
bk_plot(rbd)   # ranked colour bars with SE and letter groups

## 2. Genetic variability across several traits
traits <- c("grain_yield","plant_height","tillers","panicle_len","test_weight")
bk_plot(bk_variability(bk_data("rbd"), traits, "genotype", "rep"))

## 3. Correlation heatmap (genotypic)
bk_plot(bk_correlation(bk_data("rbd"), traits, "genotype", "rep"))

## 4. Path analysis on yield
bk_plot(bk_path(bk_data("rbd"),
        c("plant_height","tillers","panicle_len","test_weight"),
        dependent = "grain_yield", gen = "genotype", rep = "rep"))

## 5. D² divergence clusters
bk_plot(bk_diversity(bk_data("rbd"), traits, "genotype", "rep"))

## 6. Augmented alpha-lattice (unreplicated test entries + checks)
bk_plot(bk_augmented(bk_data("augmented"), "grain_yield", "genotype",
                     block = "block", rep = "rep",
                     checks = paste0("CHK-", 1:4)))

## 7. Multi-location stability — AMMI-2 biplot
bk_plot(bk_stability(bk_data("mlt"), "grain_yield",
        gen = "genotype", env = "environment", rep = "rep"))

Run everything and save all figures as PNG:

source(system.file("examples", "run_all.R", package = "BKBreed"))

Bundled example data

bk_data("rbd") pearl-millet multi-trait RBD · bk_data("frbd") N × variety factorial · bk_data("augmented") augmented alpha-lattice (4 checks + 20 test entries) · bk_data("mlt") 10 genotypes × 5 environments.

Methods & conventions

License

GPL-3. Author: Dr. Praveen Kumar B. K., Agriculture University, Jodhpur — Genetics & Plant Breeding.