ms-qc-notebook

Jupyter notebook for quality control of mass spectrometry data.

This notebook performs basic QC for proteomics experiments processed with FragPipe and raw data in mzML format.

What this notebook does

From raw mzML files:

• counts MS1 and MS2 spectra

From FragPipe results

• PSM / peptide / protein counts
• fraction of PSMs with missed cleavages
• fraction of signal intensity from missed cleavages
• enzymatic specificity (fully / semi / non-tryptic peptides)
• missed cleavage distribution
• peptide length distribution
• charge state distribution
• intensity distribution (PSM level)
• protein dynamic range

All results are visualized and summarized in a final merged table.

Dependencies

• Python>=3.12
• matplotlib
• pandas
• pyteomics
• seaborn
• numpy

Input data structure (FragPipe v23.1 automatically generated)

The notebook expects the following structure:

project/
├── raw/                       # mzML files
│   ├── sample1.mzML
│   ├── sample2.mzML
│   └── ...
│
├── results/                   # FragPipe output
│   ├── experiment_annotation.tsv
|   ├── ... 
│   ├── sample1/
│   │   ├── psm.tsv
│   │   ├── peptide.tsv
|   |   ├── protein.tsv
|   |   └── ...
│   ├── sample2/
│   │   ├── psm.tsv
│   │   ├── peptide.tsv
|   |   ├── protein.tsv
|   |   └── ...
│   └── ...

experiment_annotation.tsv must contain at least two columns: file - raw file name; sample_name - sample number in FragPipe

Run

Install dependencies:

$ pip install -r requirements.txt

At the top of the notebook set:

result_path = ''   # path to folder with FragPipe results
raw_dir_path = ''  # path to folder with mzML files
annotation_path = f'{result_path}/experiment_annotation.tsv'

Run all cells

Output

MS1/MS2 counting

Trypsinolysis QC

Summary table

Test data

Public raw data used for testing were obtained from the PRIDE repository (project PXD000498).