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Related Experiment Video

Updated: Sep 28, 2025

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
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StackZDPD: a novel encoding scheme for mass spectrometry data optimized for speed and compression ratio.

Jinyin Wang1,2,3, Miaoshan Lu1,4,3, Ruimin Wang4,5,3

  • 1Zhejiang University, Hangzhou, 310058, China.

Scientific Reports
|March 31, 2022
PubMed
Summary
This summary is machine-generated.

A new encoding scheme, Stack-ZDPD, significantly compresses mass spectrometry (MS) data, reducing mzML file sizes by over 80% while maintaining efficient data access for proteomics and metabolomics research.

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Area of Science:

  • Biochemistry
  • Computational Biology
  • Data Science

Background:

  • Mass spectrometry (MS) data, stored in mzML format, faces challenges with large file sizes and slow read/write speeds, hindering analysis.
  • Existing compression methods often lack flexible random file access, and database solutions have limited compression and software support.

Purpose of the Study:

  • To develop an efficient encoding scheme for raw MS data storage and analysis.
  • To optimize data compression for mzML files without sacrificing random file reading efficiency.

Main Methods:

  • Proposed "Stack-ZDPD" encoding scheme optimized for raw MS data storage.
  • Designed the "Aird" format for computation-oriented access with fast decoding.
  • Utilized "ZDPD" as the core compression algorithm.

Main Results:

  • Stack-ZDPD reduces mzML data volume by approximately 80% or more.
  • Achieved a 30% higher compression ratio compared to ZDPD for Time of Flight data.
  • Ensured efficient decompression and random file reading capabilities.

Conclusions:

  • Stack-ZDPD offers a significant improvement in MS data storage efficiency.
  • The Aird format and Stack-ZDPD scheme facilitate faster and more manageable proteomics and metabolomics data analysis.
  • The approach is accessible via AirdPro for conversion and Aird-SDK for parsing.