Multiomic ALS signatures highlight sex differences and molecular subclusters and identify the MAPK pathway as therapeutic target

This repository contains the analytical pipeline for the MAXOMOD project, which focuses on the multi-omic analysis of axono-synaptic degeneration in the motor neuron disease amyotrophic lateral sclerosis (ALS). The project explores sex differences and molecular subclusters in ALS and investigates the MAPK pathway as a potential therapeutic target.

For a detailed understanding of the scientific background and the findings, refer to our paper published on Nature Communications.

Table of Contents

• Getting Started
  • Prerequisites
  • Data Preparation
  • Organize Data
• Reproducing Results
• Contributing
• Collaboration

Getting Started

Prerequisites

• Git
• DVC
• Nextflow
• Container execution engine (e.g. Docker or Podman)

Clone the git repository:

git clone https://github.com/imsb-uke/MAXOMOD_Pipeline.git ./maxomod

Enter the cloned directory:

cd maxomod

Data Preparation

Human sequencing data: EGAS00001007318 [due to patient data, access is restricted]

Mouse sequencing data: GSE234246

Proteomics data: PXD043300

Phosphoproteomics data: PXD043297

Organize Data

All data should be organized in datasets using the following structures

datasets/
    consortium/
        <model>/
            01_received_data/
                <omic>/
                cohort/

The pipeline expects fastq.gz files for the sequencing data, txt files for the proteomics data and csv files for the phosphoproteomics data.

Please, use DVC to see, which exact file names are required:

dvc status srna_organize_samples proteomics_organize_samples phosphoproteomics_organize_samples rnaseq_nextflow

Automatic download (optional)

To automatically download the RNAseq & miRNAseq data we provide a download script, which can be executed using the following commands:

dvc unfreeze sra_prefetch sra_fastq_dump sra_organize
dvc repro

Reproducing Results

To reproduce the analysis results, execute the following command:

dvc repro

This command will run the predefined pipelines to process and analyze the data according to the methodology described in the associated publication. All steps will be executed in a docker container automatically using the docker_wrapper.sh script. All docker images will be automatically downloaded and are available in the Packages section on GitHub.

Contributing

We welcome contributions to enhance the reproducibility and scope of the analysis.

Collaboration

For questions or collaboration offers, please contact the project's principal investigators via email provided on the MAXOMOD project page: MAXOMOD Contact Information.