ME/CFS Cohort Analysis

This repository contains multiple complementary analyses of the Ramsey award ME/CFS cohort, including differential
gene expression analysis and phenotypic comparison studies.

Background

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a chronic and debilitating illness affecting millions of
individuals worldwide. It is characterized by severe fatigue, pain, flu-like symptoms, and cognitive issues. The cause
of ME/CFS is not well understood, but evidence suggests a genetic predisposition and dysregulation of the immune
system leading to an overactive immune response.

This repository hosts analyses that explore:

Differential gene expression patterns in ME/CFS patients
Phenotypic overlap between ME/CFS and other diseases
Patient phenotypic similarity and clustering
Disease enrichment analyses

Repository Structure

dge-analysis/ - Differential gene expression analysis using R
phenotypic-analysis/ - Phenotypic comparison analysis
variant-findings-plot/ - Variant findings plotting

Installation

Requirements

For Differential Gene Expression Analysis:

R (v4.5.1 or later)
RStudio (v2025.05.1+513 or later)

For Phenotypic Comparison Analysis and Variant Findings plot:

Anaconda3 or Mamba

Common Requirements:

Git v2.0+

Setup

Installation starts with fetching the Git repo and cloning it:

git clone https://github.com/uab-cgds-worthey/mecfs-cohort-analysis.git
cd mecfs-cohort-analysis/

For detailed setup instructions for each analysis, see the README files in their respective directories:

Differential Gene Expression Analysis: See dge-analysis/README.md for detailed
R/renv setup instructions
Phenotypic Comparison Analysis: See the phenotypic comparison documentation for
conda/mamba environment setup instructions
Variant Findings plot: See the variant findings documentation for conda/mamba
environment setup instructions

Analyses

Differential Gene Expression Analysis

The differential gene expression analysis examines transcriptional changes in a cohort of 23 patients diagnosed with
ME/CFS using bulk RNA-seq. The analysis identifies genes that are differentially expressed between
affected and unaffected conditions, and explores subgroup-specific patterns.

Located in dge-analysis/.

For detailed documentation including setup, input data, workflow instructions, and results, see
dge-analysis/README.md. The complete analysis described in the publication, generated by
subsetted_condition_analysis.Rmd, is available as an .RData file for
download and can be loaded
directly in R using load("path/to/rdata").

Results: Differential Gene Expression

Results and figures can be found in the dge-analysis/docs/ folder
Viewable online at: https://uab-cgds-worthey.github.io/mecfs-cohort-analysis/

Phenotypic Comparison Analysis

A collection of diseases found in the Ramsey award ME/CFS cohort, phenotypes of ME/CFS and those diseases, and
analysis scripts for the comparison and visualization of phenotypes between diseases.

Located in phenotypic-analysis/

For detailed documentation including setup, tools, notebooks, and analysis instructions, see
phenotypic-analysis/README.md.

Results: Phenotypic Comparison

Results and figures can be found in phenotypic-analysis/data/results/
Carruthers ME/CFS diagnositic creteria as HPO terms is defined in
phenotypic-analysis/data/mecfs-phenotypes.tsv

Variant findings plot

Organized metadata and primary variant findings organized in a variant format expected by the pyoncoprint
Python library for generating variant oncoplots. The figure generation process is described in the
plotting Jupyter notebook

Authors

Shaurita D. Hutchins 📧 | PhD Candidate
Brandon M. Wilk 📧 | PhD Candidate

License

This project is licensed under the GNU General Public License v3.0.

uab-cgds-worthey/mecfs-cohort-analysis