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This R package provides tools for analyzing condition-specific molecular sex differences in omics data. It enables identification of sex-specific, sex-dimorphic, and sex-modulated genes through differential expression and interaction analyses, accompanied by pathway enrichment and gene regulatory network analysis capabilities.
You can download the latest version of the XYomics package here:
MD5 Checksum: 2c1bba2aa8291e4edfbb0e50c86b52a4
Five main analysis modules (+ dedicated implementations for single-cell data analysis):
Differential Expression Analysis: Identifies sex-specific and sex-dimorphic genes across conditions in bulk and single-cell data.
Sex Interaction Analysis: Detects sex-modulated genes through interaction analysis in bulk and single-cell data.
Pathway Enrichment Analysis: Performs pathway analysis on sex-biased gene sets for bulk and single-cell data.
Gene Regulatory Network (GRN) Analysis: Constructs and analyzes condition-specific gene regulatory networks for single-cell data.
Plotting and Reporting Functions: Generates visualizations and comprehensive analysis reports.
Includes example datasets and supports various omics data types (RNA-seq, microarray, proteomics). Input data should be formatted as described in the vignettes.
Please find below the vignettes for the XYomics R-packages:
Required R version: ≥ 4.2.0
Key dependencies:
MIT License
apt-get install libcurl-dev libcurl4-openssl-dev libudunits2-dev libgdal-dev libharfbuzz-dev libfribidi-dev libharfbuzz-dev libfribidi-dev
install_XYpackages <- function() {
# Helper to check which packages are not installed
not_installed <- function(pkgs) {
setdiff(pkgs, rownames(installed.packages()))
}
# Ensure BiocManager is installed
if (!requireNamespace("BiocManager", quietly = TRUE)) {
install.packages("BiocManager")
}
# Install Bioconductor packages
bioc_pkgs <- c("clusterProfiler", "org.Hs.eg.db", "ReactomePA", "topGO", "edgeR", "DESeq2")
to_install <- not_installed(bioc_pkgs)
if (length(to_install) > 0) {
BiocManager::install(to_install, update = FALSE, ask = FALSE)
message(paste(to_install, collapse = ", "), " packages added...")
}
# Install CRAN helper packages
cran_pkgs <- c("devtools", "remotes", "DT", "kableExtra")
to_install_cran <- not_installed(cran_pkgs)
if (length(to_install_cran) > 0) {
install.packages(to_install_cran)
}
if (!requireNamespace("sf", quietly = TRUE)) {
os_type <- Sys.info()[["sysname"]]
message("Installing 'sf' package...")
if (os_type == "Darwin") {
# macOS
install.packages("sf", type = "binary")
} else if (os_type == "Linux" || os_type == "Windows") {
# Linux or Windows
install.packages("sf", type = "source")
} else {
warning("Unknown OS. Please install 'sf' manually.")
}
}
# Install GitHub packages if missing
github_pkgs <- list(
PCSF = "IOR-Bioinformatics/PCSF",
multienrichjam = "jmw86069/multienrichjam"
)
for (pkg in names(github_pkgs)) {
if (pkg %in% not_installed(pkg)) {
remotes::install_github(github_pkgs[[pkg]], upgrade = "never")
}
}
# Message if nothing was added
if (length(to_install) == 0 && length(to_install_cran) == 0 &&
all(!names(github_pkgs) %in% not_installed(names(github_pkgs)))) {
message("No new packages added...")
}
}
install_XYpackages()
Install from GitLab:
devtools::install_url("https://gitlab.com/uniluxembourg/lcsb/bds/xyomics/-/raw/main/XYomics_0.1.1.tar.gz")
Install from Local Download: 1. Download the package file: XYomics_0.1.1.tar.gz 2. Install using R:
install.packages(“path/to/XYomics_0.1.1.tar.gz”, repos = NULL, type = “source”)
The package installation is tested on the following operating systems - Windows 11 - MAC OS - Ubuntu 20.4
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.
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