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StackZDPD: a novel encoding scheme for mass spectrometry data optimized for speed and compression ratio
As the pervasive, standardized format for interchange and deposition of raw mass spectrometry (MS) proteomics and metabolomics data, text-based mzML is inefficiently utilized on various analysis platforms due to its sheer volume of samples and limited read/write speed. Most research on compression a...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8967824/ https://www.ncbi.nlm.nih.gov/pubmed/35354909 http://dx.doi.org/10.1038/s41598-022-09432-1 |
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author | Wang, Jinyin Lu, Miaoshan Wang, Ruimin An, Shaowei Xie, Cong Yu, Changbin |
author_facet | Wang, Jinyin Lu, Miaoshan Wang, Ruimin An, Shaowei Xie, Cong Yu, Changbin |
author_sort | Wang, Jinyin |
collection | PubMed |
description | As the pervasive, standardized format for interchange and deposition of raw mass spectrometry (MS) proteomics and metabolomics data, text-based mzML is inefficiently utilized on various analysis platforms due to its sheer volume of samples and limited read/write speed. Most research on compression algorithms rarely provides flexible random file reading scheme. Database-developed solution guarantees the efficiency of random file reading, but nevertheless the efforts in compression and third-party software support are insufficient. Under the premise of ensuring the efficiency of decompression, we propose an encoding scheme “Stack-ZDPD” that is optimized for storage of raw MS data, designed for the format “Aird”, a computation-oriented format with fast accessing and decoding time, where the core compression algorithm is “ZDPD”. Stack-ZDPD reduces the volume of data stored in mzML format by around 80% or more, depending on the data acquisition pattern, and the compression ratio is approximately 30% compared to ZDPD for data generated using Time of Flight technology. Our approach is available on AirdPro, for file conversion and the Java-API Aird-SDK, for data parsing. |
format | Online Article Text |
id | pubmed-8967824 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-89678242022-04-01 StackZDPD: a novel encoding scheme for mass spectrometry data optimized for speed and compression ratio Wang, Jinyin Lu, Miaoshan Wang, Ruimin An, Shaowei Xie, Cong Yu, Changbin Sci Rep Article As the pervasive, standardized format for interchange and deposition of raw mass spectrometry (MS) proteomics and metabolomics data, text-based mzML is inefficiently utilized on various analysis platforms due to its sheer volume of samples and limited read/write speed. Most research on compression algorithms rarely provides flexible random file reading scheme. Database-developed solution guarantees the efficiency of random file reading, but nevertheless the efforts in compression and third-party software support are insufficient. Under the premise of ensuring the efficiency of decompression, we propose an encoding scheme “Stack-ZDPD” that is optimized for storage of raw MS data, designed for the format “Aird”, a computation-oriented format with fast accessing and decoding time, where the core compression algorithm is “ZDPD”. Stack-ZDPD reduces the volume of data stored in mzML format by around 80% or more, depending on the data acquisition pattern, and the compression ratio is approximately 30% compared to ZDPD for data generated using Time of Flight technology. Our approach is available on AirdPro, for file conversion and the Java-API Aird-SDK, for data parsing. Nature Publishing Group UK 2022-03-30 /pmc/articles/PMC8967824/ /pubmed/35354909 http://dx.doi.org/10.1038/s41598-022-09432-1 Text en © The Author(s) 2022, corrected publication 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Wang, Jinyin Lu, Miaoshan Wang, Ruimin An, Shaowei Xie, Cong Yu, Changbin StackZDPD: a novel encoding scheme for mass spectrometry data optimized for speed and compression ratio |
title | StackZDPD: a novel encoding scheme for mass spectrometry data optimized for speed and compression ratio |
title_full | StackZDPD: a novel encoding scheme for mass spectrometry data optimized for speed and compression ratio |
title_fullStr | StackZDPD: a novel encoding scheme for mass spectrometry data optimized for speed and compression ratio |
title_full_unstemmed | StackZDPD: a novel encoding scheme for mass spectrometry data optimized for speed and compression ratio |
title_short | StackZDPD: a novel encoding scheme for mass spectrometry data optimized for speed and compression ratio |
title_sort | stackzdpd: a novel encoding scheme for mass spectrometry data optimized for speed and compression ratio |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8967824/ https://www.ncbi.nlm.nih.gov/pubmed/35354909 http://dx.doi.org/10.1038/s41598-022-09432-1 |
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