CLAW-MRM

CLAW-MRM (Comprehensive Lipidomics Automation Workflow) - a pipeline for processing and analyzing MRM (Multiple Reaction Monitoring) lipidomics data.

Created by: Sanjay Iyer

Overview

CLAW-MRM is designed to streamline the analysis of MRM-based lipidomics experiments. In this tutorial we will parse mzML data and format in organized pandas DataFrames and export as csv files. We will also reformat this data for various tools such as EdgeR (differential expression) and pathway analysis.

Repository Structure

CLAW_MRM/
├── CLAW_MRM_tutorial.ipynb          # Tutorial Jupyter notebook
├── README.md
├── scripts/                     # Core analysis scripts
│   ├── CLAW.py                  # Main CLAW processing script
│   ├── CLAW_preedgeR.py         # Pre-EdgeR formatting script
│   └── CLAW_pathwayanalysis.py  # Pathway analysis formatting
├── lipid_database/              # Reference databases
│   ├── Custom_MRM.csv           # Custom MRM transitions
│   └── Lipid_Database.xlsx      # Lipid reference database
├── projects/                    # Project directories
│   └── lipid_load/              # Example project
│       ├── mzml/                # mzML data files
│       ├── labels/              # Sample metadata & labels
│       ├── results/             # CLAW output results
│       ├── pre_edger/           # EdgeR-formatted data
│       └── pathway_analysis/    # Pathway analysis formatted data
│     
├── CLAW_MRM/                    # CLAW MRM source code

Getting Started

Prerequisites

• Python 3.9+ (recommend using Python 3.11+ for best performance)
• Required packages: pandas, numpy, pymzml, matplotlib, openpyxl

Environment Setup

Create a conda environment with all required dependencies:

# Using default name "CLAW"
conda env create -f requirements/CLAW.yml

# Or specify a custom environment name (make any name you want in place of my_custom_name)
conda env create -f requirements/CLAW.yml -n my_custom_name 

# Activate the environment
conda activate CLAW  # or your custom name

Quick Start

1. Open CLAW_MRM_tutorial.ipynb in Jupyter
2. Follow the step-by-step instructions for:
   • Loading and processing mzML files
   • Matching lipids against the custom MRM database
   • Generating pre-EdgeR formatted files
   • Creating Pathway Analysis input files

Scripts

Script	Description
CLAW.py	Main processing script for mzML files and lipid matching
CLAW_preedgeR.py	Formats intensity data for EdgeR differential analysis
CLAW_pathwayanalysis.py	Generates pathway analysis formatted output

📊 PreEdgeR and Pathway Analysis

Overview

These modules perform formatting for EdgeR and pathway enrichment

Requirements

Experimental Design

• Minimum: 3 biological replicates per group
• Recommended: 5+ biological replicates per group for increased statistical power
• Groups: At least 2 groups (e.g., Treatment vs Control, Disease vs Healthy)

⚠️ Important: More replicates = more robust statistical results and better detection of true differences

Data Format

Your data must include:

• Labels file (labels.csv): Sample metadata with group assignments
  • Example columns: Sample_ID, Genotype (or other grouping factor)
• Intensity file: Lipid measurements across samples
  • Must contain: Lipid, Sample_ID, Intensity columns

Example Group Comparison

Group A (Control): WT samples     → 3-8 replicates
Group B (Treatment): 5XFAD samples → 3-8 replicates

Contact

For questions or collaboration:

• Sanjay Iyer - iyer95@purdue.edu
• Chopra Lab - choprait@purdue.edu