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Related Experiment Video

Updated: Feb 4, 2026

Proteomic Profile of EPS-Urine through FASP Digestion and Data-Independent Analysis

Published on: May 8, 2021

A Data Analysis Protocol for Quantitative Data-Independent Acquisition Proteomics.

Sami Pietilä¹, Tomi Suomi¹, Juhani Aakko¹

¹Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Turku, Finland.

Methods in Molecular Biology (Clifton, N.J.)

|October 3, 2018

Summary

This summary is machine-generated.

We present diatools, a free, open-source protocol for analyzing data-independent acquisition (DIA) mass spectrometry proteomics data. This comprehensive workflow simplifies spectral library construction to differential expression analysis for accurate protein quantification.

Keywords:

DDA DIA Data analysis Mass spectrometry Proteomics SWATH-MS Spectral library

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Quantification of Site-specific Protein Lysine Acetylation and Succinylation Stoichiometry Using Data-independent Acquisition Mass Spectrometry

Quantification of Site-specific Protein Lysine Acetylation and Succinylation Stoichiometry Using Data-independent Acquisition Mass Spectrometry

Published on: April 4, 2018

Related Experiment Videos

Last Updated: Feb 4, 2026

Proteomic Profile of EPS-Urine through FASP Digestion and Data-Independent Analysis

Published on: May 8, 2021

Data Acquisition Protocol for Determining Embedded Sensitivity Functions

Data Acquisition Protocol for Determining Embedded Sensitivity Functions

Published on: April 20, 2016

Quantification of Site-specific Protein Lysine Acetylation and Succinylation Stoichiometry Using Data-independent Acquisition Mass Spectrometry

Quantification of Site-specific Protein Lysine Acetylation and Succinylation Stoichiometry Using Data-independent Acquisition Mass Spectrometry

Published on: April 4, 2018

Area of Science:

Proteomics
Mass Spectrometry
Bioinformatics

Background:

Data-independent acquisition (DIA) mass spectrometry, including SWATH-MS, offers precise protein quantification vital for comparative proteomics.
Existing data analysis workflows for DIA proteomics are often proprietary, complex, or lack comprehensive integration.
A need exists for accessible, end-to-end solutions for processing and analyzing DIA-MS data.

Purpose of the Study:

To introduce diatools, a novel, open-source data analysis protocol for DIA proteomics.
To provide a user-friendly, integrated workflow from raw spectral data to differential expression analysis.
To ensure broad accessibility across different operating systems via a Dockerized environment.

Main Methods:

Development of a comprehensive data analysis protocol (diatools) for DIA proteomics.
Integration of open-source tools for spectral library building, peptide intensity matrix generation, and downstream analysis.
Containerization of the entire workflow using Docker for cross-platform compatibility (Linux, Windows, macOS).

Main Results:

The diatools protocol successfully integrates multiple data processing steps for DIA-MS.
The protocol is implemented using open-source software, ensuring free accessibility.
A Dockerized environment facilitates easy implementation on various operating systems.

Conclusions:

diatools provides a robust, accessible, and integrated solution for DIA proteomics data analysis.
This protocol addresses the current limitations in free and easy-to-implement DIA-MS data processing.
The widespread availability of diatools will facilitate advancements in comparative proteomics research.