quantms: a cloud-based pipeline for quantitative proteomics enables the reanalysis of public proteomics data

Area of Science:

• Proteomics
• Bioinformatics
• Computational Biology

Background:

• The rapid growth of public proteomics data presents significant computational challenges for large-scale reanalysis.
• Efficient and reproducible analysis of this data is crucial for advancing biological insights.

Purpose of the Study:

• To introduce quantms, an open-source cloud-based pipeline designed for massively parallel proteomics data analysis.
• To address the computational challenges posed by the increasing volume of public proteomics datasets.

Main Methods:

• Development and application of quantms, a cloud-based pipeline utilizing standard file formats.
• Reanalysis of 83 public ProteomeXchange datasets, including 29,354 instrument files from 13,132 human samples.

Main Results:

• Quantification of 16,599 proteins based on 1.03 million unique peptides across the analyzed datasets.
• Demonstration of quantms' capability for large-scale, parallelized proteomics data processing.

Conclusions:

• quantms provides a robust solution for the reanalysis of large-scale public proteomics data.
• The pipeline improves data reproducibility, submission, and dissemination through its adherence to standard file formats and integration with ProteomeXchange.