panGenomeBreedr (panGB) is conceptualized to be a unified, crop
agnostic platform for pangenome-enabled breeding that follows
standardized conventions for natural or casual variant analysis using
pangenomes, marker design, and marker QC hypothesis testing (Figure 1).
It seeks to simplify and enhance the use of pangenome resources in
cultivar development.
Fig. 1. Conceptual workflow of the panGenomeBreedr (panGB) package for pangenome-enabled marker development. Using snpEff-annotated VCF files organized within a SQLite database, panGB enables querying for variants within candidate genes or user-defined genomic regions. It retrieves mutation annotations and predicted impacts from snpEff to identify putative causal variants (PCVs), which serve as the basis for designing functional trait-predictive markers. The package supports hypothesis-driven validation of these markers and also facilitates the design of additional marker types, including precision-introgression and background markers.
In its current development version, panGB provides customizable R functions for variant discovery from snpEff-annotated VCF files, KASP marker design, and marker validation (Steps 1–3 in Fig. 1).
To expand accessibility, panGB will include a user-friendly Shiny
application, allowing non-R users to leverage its core features without
requiring R programming experience.
The SNP Viewer tool by LGC Genomics is limited to Windows platforms and
lacks standardized conventions for visualizing positive controls in
marker validation, making it difficult for users to conclusively assess
marker performance. In contrast, panGB offers platform-independent
tools for hypothesis testing, quality control (QC), and validation of
KASP markers, addressing a key gap in existing visualization and
validation workflows.
Submit bug reports and feature suggestions, or track changes on the issues page.
To use this package locally on a machine, the following R packages are required:
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Rtools: Needed for package development and installation from GitHub on Windows PCs.
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UpSetR: Required for generating UpSet plots.
First, ensure all existing packages are up to date.
You can install the development version of panGenomeBreedr from
GitHub with:
# Install panGenomeBreedr
if (!require("devtools")) install.packages("devtools")
devtools::install_github("awkena/panGenomeBreedr")panGB depends on a list of Bioconductor packages that may not be
installed automatically alongside panGB. To manually install these
packages, use the code snippet below:
# Install and load required Bioconductor packages if not already installed
if (!require("BiocManager", quietly = TRUE)) install.packages("BiocManager")
# Define required Bioconductor packages
bioc_packages <- c("rtracklayer", "Rsamtools", "msa", "IRanges",
"GenomicRanges", "BSgenome", "Biostrings")
# Install any missing Bioconductor packages
for (pkg in bioc_packages) {
if (!requireNamespace(pkg, quietly = TRUE)) {
BiocManager::install(pkg, ask = FALSE, update = FALSE)
}
}panGB currently provides functionality for the following key tasks:
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Variant discovery
Identify variants within candidate genes or any user-defined genomic interval using snpEff-annotated VCF files. -
KASP marker design
Generate allele-specific markers targeting either causal variants or any variant of interest. -
Marker validation and QC visualization
Produce quality control plots and perform hypothesis-driven evaluations to assess marker reliability. -
Decision-support for trait introgression
Guide marker-assisted backcrossing by profiling foreground, background, and precision-introgression markers to support selection decisions.
👉 For a full tutorial and worked example, check out the panGenomeBreedr Workflow vignette.
If the package does not run as expected, check the following:
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Was the package properly installed?
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Do you have the required dependencies installed?
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Were any warnings or error messages returned during package installation?
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Are all packages up to date before installing panGB?
For support and submission of feedback, email the maintainer Alexander Kena, PhD at alex.kena24@gmail.com