About

Code and data to reproduce figures in the FunGen-xQTL phase 1 manuscript.

FunGen-xQTL Overview

This project focuses on functional genomics and expression quantitative trait loci (xQTL) analysis. The xQTL approach integrates multi-omics data to understand regulatory architecture and genetic influences on molecular phenotypes.

For a list of data and resources from our project please check out https://statfungen.github.io/xqtl-resources/#fungen-xqtl

Repository Structure

This repository contains the codes and data used to generate all figures from our manuscript, available at: https://github.com/StatFunGen/xqtl-paper

The repository is organized as follows:

Main Text Structure

main_text/
├── 1_project_overview/
│   ├── index.md (FunGen-xQTL atlas and companion projects)
│   └── figure_data/README.md (Data for figures)
├── 2_single_context_cis/
│   ├── index.md (Single context cis-xQTL fine-mapping)
│   └── figure_data/README.md (Data for figures)
├── 3_single_context_multigene_trans/
│   ├── index.md (Multi-gene and trans-xQTL fine-mapping)
│   └── figure_data/README.md (Data for figures)
├── 4_multi_context/
│   ├── index.md (Propagation of multi-context xQTL effects)
│   └── figure_data/README.md (Data for figures)
├── 5_AD_xQTL_integration/
│   ├── index.md (Alzheimer's disease loci integration)
│   ├── Figure_5a_AD_GWAS_loci_harmonized.ipynb
│   ├── Figure_5b_AD_GWAS_loci_properties.ipynb
│   ├── Figure_5c_AD_loci_xQTL_annotated.ipynb
│   └── figure_data/README.md (Data for figures)
└── 6_AD_xQTL_genes/
    ├── index.md (Insights into AD risk genes)
    └── figure_data/README.md (Data for figures)

Additional Content

• supplementary_tables/: Supplementary data tables
• website/: Configuration files for the interactive Jupyter Book website
• references.bib: Bibliography file for citations
• setting_up.md: Setup instructions for the Jupyter Book environment

Each figure_data folder contains RDS format data files with the minimum information necessary to reproduce plot figures, allowing users to check numerical values.

Website

https://statfungen.github.io/xqtl-paper

To navigate this resource, use the table of contents in the left sidebar of the website. Each notebooks allow you to:

1. View the code used to generate analyses
2. Examine data associated with the figures
3. Reproduce visualizations

For detailed setup instructions and environment configuration to generate the website, see our Website Setup Guide.

Computational Requirements

The analyses in this repository are performed using:

• Python 3.9 or higher
• R version 4.1 or higher
• Key packages: jupyter-book, ggplot2

Citation

If you use resources from this repository in your research, please cite our manuscript (citation details will be added upon publication).