DOI: 10.5281/zenodo.15830989
title: Complete Computational Workflow for Integrated PTM and Total Proteome Analysis: Distinguishing Expression from Usage Changes

description: # PTM Analysis Example: Complete Computational Workflow


**Version:** 1.0

**Date:** July 2025

**DOI:** [Add Zenodo DOI here]


## Overview


This repository contains a complete, executable example of the computational workflow for integrated post-translational modification (PTM) and total proteome analysis described in our manuscript "Integrated Analysis of Post-Translational Modifications and Total Proteome: Methods for Distinguishing Expression from Usage Changes".


The analysis demonstrates how to distinguish between **Differential PTM Expression (DPE)** - changes in PTM abundance due to protein expression changes - and **Differential PTM Usage (DPU)** - true changes in modification stoichiometry independent of protein abundance.


## Dataset Description


The example uses the Atg16l1 macrophage dataset from Maculins et al. (eLife 2021), investigating autophagy responses to bacterial infection:


- **Experimental Design**: 2×3 factorial (Genotype: WT/KO × Timepoint: Uninfected/Early/Late infection)

- **Technology**: TMT 11-plex quantitative proteomics

- **Sample Type**: Mouse bone marrow-derived macrophages

- **Conditions**: Wild-type vs Atg16l1-knockout cells infected with Shigella


## Repository Contents


### 📁 Core Analysis Scripts

- `prolfqua_dataset.sh` - Dataset annotation creation

- `prolfqua_dea.sh` - Differential expression analysis wrapper

- `prolfqua_qc.sh` - Quality control analysis wrapper

- `prolfqua_yaml.sh` - Configuration setup

- `config.yaml` - Analysis configuration parameters


### 📊 Quality Control Reports

- `QCReport.html` - Comprehensive QC analysis of TMT data including:

- Database composition analysis

- TMT labeling efficiency assessment

- Missed cleavage analysis

- Quantitative channel balance evaluation


### 📈 Differential Expression Analysis Results


#### Total Proteome Analysis (`DEA_20250715_WUtotal_proteome_vsn/`)

- `index.html` - Analysis overview

- `Results_WU_total_proteome/`

- `DE_WUtotal_proteome.html` - Interactive differential expression report

- `DE_WUtotal_proteome.xlsx` - Complete statistical results

- `QC_WUtotal_proteome.html` - Quality control metrics

- `GSEA_*.rnk` - Gene set enrichment analysis input files

- `ORA_*.txt` - Over-representation analysis results


#### Single-site PTM Analysis (`DEA_20250715_WUsinglesite_PTM_vsn/`)

- Individual phosphorylation site-level analysis

- Site-specific statistical testing and visualization


#### Multi-site PTM Analysis (`DEA_20250715_WUmultisite_PTM_vsn/`)

- Peptide-level PTM pattern analysis

- Multi-site modification coordination assessment


### 🔬 Integrated PTM Analysis Results (`PTM_analysis_20250715_singlesite_CustomPhosphoAnalysis/`)


#### Key Output Files:

- **`Result_phosphoAndTotalIntegration.html`** - Interactive integrated analysis report with:

- DPE vs DPU comparison tables

- N-to-C sequence visualization plots

- Statistical summaries and quality metrics

 

- **`Result_phosphoAndTotalIntegration.xlsx`** - Complete statistical results including:

- Combined PTM and protein statistics

- DPU calculations with p-values and FDR correction

- Site-level annotations and sequence windows


- **`Site_differential_Expression.pdf`** - N-to-C plots showing PTM sites along protein sequences with expression changes


- **`Site_differential_UsageChange.pdf`** - N-to-C plots showing protein-normalized PTM usage changes


### 📖 Documentation and Source Code

- `Supplementary_Material_v2.html` - Complete analysis walkthrough

- `Supplementary_Material_v2.pdf` - PDF version of the analysis guide

- `dataset_with_contrasts.tsv` - Experimental design annotation


## Software Requirements


### R Environment

- **R version**: ≥ 4.0.0

- **System requirements**: 8GB+ RAM (16GB+ recommended), 5GB+ storage


### Required R Packages

- `prolfqua` (doi:10.1021/acs.jproteome.2c00441) - Statistical framework

- `prolfquapp` (doi:10.1021/acs.jproteome.4c00911) - Differential expression pipeline

- `prolfquappPTMreaders` (doi:10.5281/zenodo.15845243) - PTM data readers

- `prophosqua` (doi:10.5281/zenodo.15845272) - PTM integration and visualization

- `tidyverse`, `ggseqlogo`, `writexl`, `rmarkdown` - Data manipulation and reporting


## How to Use This Example


### 1. **Explore the Results**

Start by opening the main results files:

- `QCReport.html` - Understand data quality

- `DEA_*/Results_*/DE_*.html` - Review differential expression results

- `Supplementary_Material_v2.html` - Understand the analysis methodology

- `Result_phosphoAndTotalIntegration.html` - Examine integrated analysis


### 2. **Reproduce the Analysis**


For details see https://github.com/prolfqua/prophosqua/


### 3. **Adapt to Your Data**

Modify the analysis parameters in:

- `config.yaml` - Analysis settings

- `dataset_with_contrasts.tsv` - Experimental design

- Script parameters for your file paths and conditions


### 4. **Understand the Methodology**

The `Supplementary_Material_v2.html` provides a complete step-by-step walkthrough including:

- Data preprocessing and quality control

- Statistical analysis frameworks

- Integration methodology for PTM and protein data

- Biological interpretation guidelines


## Key Analysis Concepts


### Differential PTM Expression (DPE)

Tests raw PTM-feature changes between conditions without protein normalization. Identifies any modification whose abundance changes, including those driven by protein expression changes.


### Differential PTM Usage (DPU)

Tests protein-normalized PTM changes, revealing modification sites where stoichiometry genuinely changes independent of protein abundance. This analysis identifies true signaling changes.


### N-to-C Plots

Visualizations showing PTM sites along protein sequences in their biological context, facilitating interpretation by displaying modifications relative to known domains and functional regions.


## File Size Information

- **Total size**: ~700 MB (compressed)

- **Largest files**:

- Excel results files: 50-65 MB each

- HTML reports: 15-36 MB each

- PDF visualizations: 100-130 KB each


## Citation


If you use this example in your research, please cite:


[10.5281/zenodo.15830989](https://doi.org/10.5281/zenodo.15830989)


## Support and Contact


For questions about this analysis example:

- **Issues with DEA example**: [GitHub repository](https://github.com/prolfqua/prolfquapp/issues)

- **Issues with PTM analysis example**: [GitHub repository](https://github.com/prophosqua/issues)


## License


This example analysis is provided under [Creative Commons Attribution 4.0 International](https://creativecommons.org/licenses/by/4.0/) license. The underlying R packages have their own licenses as specified in their respective repositories.


## Acknowledgments


This example is based on the dataset from Maculins et al. (eLife 2021) doi:10.7554/elife.62320. We thank the authors for making their data publicly available for method development and validation.


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**Keywords**: proteomics, post-translational modifications, phosphoproteomics, TMT, differential expression, R, bioinformatics, mass spectrometry