Unveiling the Depths of Genomic Data, Layer by Layer.
Layered Exploratory Omics (LEO) is a tool specifically designed for deep analysis of genomic data. It employs a multi-layered exploratory approach to help researchers (mostly myself) uncover the complex biological information hidden behind their data. Combining cutting-edge statistical and computational methodologies, LEO offers a user-friendly interface and powerful data-processing capabilities, enabling users ranging from beginners to advanced to effectively explore and analyze their omics data.
LEO is currently in the early stages of development. We welcome feedback from developers, researchers, and users to help improve the product. Please note that some features may not be fully stable yet, and interfaces may change based on user feedback.
Method 1: via r-universe (Recommended)
# Enable the r-universe repository
options(repos = c(
laleoarrow = 'https://laleoarrow.r-universe.dev',
CRAN = 'https://cloud.r-project.org'))
# Install leo.gwas
install.packages('leo.gwas')Method 2: via GitHub
devtools::install_github("laleoarrow/leo.gwas", dependencies = TRUE)
# or
pak::pkg_install("laleoarrow/leo.gwas", dependencies = TRUE)We encourage and welcome contributions to LEO from the community. If you are interested in contributing code or documentation, please contact me by submitting a issue. Please follow the project development specification in CONTRIBUTING.md.
LEO is proprietary software. All rights reserved. Please refer to the LICENSE file for terms and restrictions.
For more information or assistance, please contact us at Ao Lu.
If you use leo.gwas in your work, please cite:
citation("leo.gwas")@Manual{leo.gwas,
title = {leo.gwas: Layered Exploratory Omics (LEO)},
author = {Ao Lu},
year = {2026},
note = {R package version 0.0.2},
url = {https://laleoarrow.github.io/leo.gwas/}
}We look forward to collaborating with researchers and developers worldwide to advance innovation and progress in genomic data analysis!