Lead Scientist: Dr. William G Ryan V Last Updated: February 11, 2026 Status: [Draft]
This repository provides a standardized, configuration-driven framework for integrating high-dimensional multi-modal data (e.g., RNA-seq, Proteomics, etc.). The purpose of utilizing Quarto (.qmd) in this pipeline is to transform raw data into a fully documented, publication-ready HTML or PDF reports.
You do not need to rewrite the analysis code. Follow these steps to generate your report:
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Use the Template, Download, and Navigate to Folder: a. Navigate to https://github.com/CogDisResLab/MultiomicMenu b. Click "Use this template" on the upper right corner of the page. c. Choose a name for your repository. Remember to make it private for sensitive data. d. Use git clone on your new repository:
git clone `git clone [https://github.com/](https://github.com/)[username]/[repo-name].git` cd [repo-name]
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Environment Setup: Open R in the project working directory and restore the required package versions:
if (!require("renv")) install.packages("renv") renv::restore()
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Configure: Edit
index.qmdwith the following important details: a. title b. species c. gmt (MUST be changed if not using human data) d. data -> value -> data files -
Render: Execute the pipeline via the terminal:
quarto render .
index.qmd: The Single Source of Truth. Define all hyperparameters and file paths here.data/: Put your DEGs, DPPs, DAPs, or DAKs here.learn.qmd: Nothing is altered here: this is for informational purposes.data.qmd: All data processing is done in this step, including integration and PPI generation using Kinograte.pathways.qmd: All pathway data is processed here using PAVER.networks.qmd: Network diagrams are generated here using igraph.
The pipeline logic is controlled entirely by the config.yaml file. Common parameters include:
| Parameter | Description | Default/Example |
|---|---|---|
title |
Title used in the final report headers. | "MultiomicMenu Report" |
species |
Species used in the experiment. | [human, rat, or mouse] |
gmt |
GMT file to use for pathway information. | gmt: "https://download.baderlab.org/EM_Genesets/current_release/Human/symbol/Human_GO_AllPathways_noPFOCR_with_GO_iea_February_03_2026_symbol.gmt" |
data |
Data files to use. | ["kinase_stk: 'data/kinase.csv'"] |
The integration primarily utilizes Prize Collecting Steiner Forest (PCSF) analysis with a PPI graph.
- R: ≥ 4.5.0
- Quarto CLI: System-level installation required (Download).
- Memory: 8GB+ RAM required. 16GB+ RAM recommended.
Upon completion, the results/ directory will contain:
index.html: An interactive report featuring all of the below pages.learn.html: A page dedicated to describing the statistics and bioinformatics of MultiomicMenu.data.html: A page for describing the data, including a "prize plot" which shows the cumulative distribution of "prizes".pathways.html: A page for pathways that are hits in the analysis.networks.html: A concatenation of all networks generated in the analysis, typically including a sample network and a seeded network.