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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.
| 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).
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.
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"))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.
GPL-3. Author: Dr. Praveen Kumar B. K., Agriculture University, Jodhpur — Genetics & Plant Breeding.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.