Description
Machine Learning for Integrating Partially Overlapped Genetic Datasets.
Description
Tools to simulate genetic distance matrices, align and compare them via multidimensional scaling (MDS) and Procrustes, and evaluate imputation with the Bootstrapping Evaluation for Structural Missingness Imputation (BESMI) framework. Methods align with Zhu et al. (2025) <doi:10.3389/fpls.2025.1543956> and the associated software resource Zhu (2025) <doi:10.26188/28602953>.
README.md
DataFusionGDM
Machine Learning Solutions for Integrating Partially Overlapped Genetic Datasets.
How to cite
If you use DataFusion-GDM, please cite:
- Paper: Zhu J., Malmberg M.M., Shinozuka M., Retegan R.M., Cogan N.O., Jacobs J.L., Giri K., Smith K.F. (2025). Machine learning solutions for integrating partially overlapping genetic datasets and modelling host–endophyte effects in ryegrass (Lolium) dry matter yield estimation. Frontiers in Plant Science. https://doi.org/10.3389/fpls.2025.1543956
- Software: Zhu, J. (2025). DataFusion-GDM. The University of Melbourne. Software. https://doi.org/10.26188/28602953
Author ORCID: https://orcid.org/0000-0002-9916-9732
Install
In R:
if (!requireNamespace("remotes", quietly = TRUE)) install.packages("remotes")
remotes::install_github("jiashuaiz/DataFusion-GDM")
Usage
library(DataFusionGDM)
# Simulate a GDM in memory and visualize
res <- run_genetic_scenario("island", n_pops = 40)
res$plots$heatmap()
res$plots$mds()
# Optionally export to CSV if needed (defaults to tempdir)
tmp <- export_simulated_gdm(scenario = "default", n_pops = 40, verbose = FALSE)
# unlink(tmp) # clean up when finished
# Simulate and visualize
source(system.file("examples/simulate_gdm_quick.R", package = "DataFusionGDM"), echo = TRUE)
# MDS + Procrustes
source(system.file("examples/mds_procrustes_demo.R", package = "DataFusionGDM"), echo = TRUE)
# BESMI batch (small demo)
source(system.file("examples/besmi_batch_quick.R", package = "DataFusionGDM"), echo = TRUE)
Vignettes
See the package vignettes for end-to-end guides:
- Getting started
- MDS + Procrustes sensitivity
- BESMI batch imputation
Open vignettes in R:
browseVignettes("DataFusionGDM")
vignette("getting-started", package = "DataFusionGDM")
Contents
- Simulation and visualization APIs in
R/simulate_gdm.R - MDS & Procrustes APIs in
R/mds_procrustes.R - BESMI preparation and imputation APIs in
R/besmi*.R - Vignettes under
vignettes/(no bundled data; examples use in-memory/temp files)
License
GPL-3.0