mzMD: visualization-oriented MS data storage and retrieval

Runmin Yang; Jingjing Ma; Shu Zhang; Yu Zheng; Lusheng Wang; Daming Zhu

doi:10.1093/bioinformatics/btac098

mzMD: visualization-oriented MS data storage and retrieval

Runmin Yang, Jingjing Ma, Shu Zhang, Yu Zheng, Lusheng Wang^*, Daming Zhu^*

^*Corresponding author for this work

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

Abstract

Motivation : Drawing peaks in a data window of an MS dataset happens at all time in MS data visualization applications. This asks to retrieve from an MS dataset some selected peaks in a data window whose image in a display window reflects the visual feature of all peaks in the data window. If an algorithm for this purpose is asked to output high-quality solutions in real time, then the most fundamental dependence of it is on the storage format of the MS dataset.
Results : We present mzMD, a new storage format of MS datasets and an algorithm to query this format of a storage system for a summary (a set of selected representative peaks) of a given data window. We propose a criterion Q-score to examine the quality of data window summaries. Experimental statistics on real MS datasets verified the high speed of mzMD in retrieving high-quality data window summaries. mzMD reported summaries of data windows whose Q-score outperforms those mzTree reported. The query speed of mzMD is the same as that of mzTree whereas its query speed stability is better than that of mzTree.

Original language	English
Article number	btac098
Pages (from-to)	2333–2340
Journal	Bioinformatics
Volume	38
Issue number	5
Online published	16 Feb 2022
DOIs	https://doi.org/10.1093/bioinformatics/btac098
Publication status	Published - 15 Apr 2022

Funding

This work was supported by Natural Science Foundation of China [No. 61732009]. Dr L.W. was supported by Natural Science Foundation of China [No. 61972329] and GRF grants for Hong Kong Special Administrative Region, P. R. China (CityU 11210119 and CityU 11206120).

Research Keywords

MASS-SPECTROMETRY
LC-MS/MS
PROTEOMICS
PLATFORM
FORMAT

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@article{c89dceebd29741ce872185dd3f057795,

title = "mzMD: visualization-oriented MS data storage and retrieval",

abstract = "Motivation : Drawing peaks in a data window of an MS dataset happens at all time in MS data visualization applications. This asks to retrieve from an MS dataset some selected peaks in a data window whose image in a display window reflects the visual feature of all peaks in the data window. If an algorithm for this purpose is asked to output high-quality solutions in real time, then the most fundamental dependence of it is on the storage format of the MS dataset.Results : We present mzMD, a new storage format of MS datasets and an algorithm to query this format of a storage system for a summary (a set of selected representative peaks) of a given data window. We propose a criterion Q-score to examine the quality of data window summaries. Experimental statistics on real MS datasets verified the high speed of mzMD in retrieving high-quality data window summaries. mzMD reported summaries of data windows whose Q-score outperforms those mzTree reported. The query speed of mzMD is the same as that of mzTree whereas its query speed stability is better than that of mzTree.",

keywords = "MASS-SPECTROMETRY, LC-MS/MS, PROTEOMICS, PLATFORM, FORMAT",

author = "Runmin Yang and Jingjing Ma and Shu Zhang and Yu Zheng and Lusheng Wang and Daming Zhu",

year = "2022",

month = apr,

day = "15",

doi = "10.1093/bioinformatics/btac098",

language = "English",

volume = "38",

pages = "2333–2340",

journal = "Bioinformatics",

issn = "1367-4803",

publisher = "Oxford University Press",

number = "5",

}

TY - JOUR

T1 - mzMD

T2 - visualization-oriented MS data storage and retrieval

AU - Yang, Runmin

AU - Ma, Jingjing

AU - Zhang, Shu

AU - Zheng, Yu

AU - Wang, Lusheng

AU - Zhu, Daming

PY - 2022/4/15

Y1 - 2022/4/15

N2 - Motivation : Drawing peaks in a data window of an MS dataset happens at all time in MS data visualization applications. This asks to retrieve from an MS dataset some selected peaks in a data window whose image in a display window reflects the visual feature of all peaks in the data window. If an algorithm for this purpose is asked to output high-quality solutions in real time, then the most fundamental dependence of it is on the storage format of the MS dataset.Results : We present mzMD, a new storage format of MS datasets and an algorithm to query this format of a storage system for a summary (a set of selected representative peaks) of a given data window. We propose a criterion Q-score to examine the quality of data window summaries. Experimental statistics on real MS datasets verified the high speed of mzMD in retrieving high-quality data window summaries. mzMD reported summaries of data windows whose Q-score outperforms those mzTree reported. The query speed of mzMD is the same as that of mzTree whereas its query speed stability is better than that of mzTree.

AB - Motivation : Drawing peaks in a data window of an MS dataset happens at all time in MS data visualization applications. This asks to retrieve from an MS dataset some selected peaks in a data window whose image in a display window reflects the visual feature of all peaks in the data window. If an algorithm for this purpose is asked to output high-quality solutions in real time, then the most fundamental dependence of it is on the storage format of the MS dataset.Results : We present mzMD, a new storage format of MS datasets and an algorithm to query this format of a storage system for a summary (a set of selected representative peaks) of a given data window. We propose a criterion Q-score to examine the quality of data window summaries. Experimental statistics on real MS datasets verified the high speed of mzMD in retrieving high-quality data window summaries. mzMD reported summaries of data windows whose Q-score outperforms those mzTree reported. The query speed of mzMD is the same as that of mzTree whereas its query speed stability is better than that of mzTree.

KW - MASS-SPECTROMETRY

KW - LC-MS/MS

KW - PROTEOMICS

KW - PLATFORM

KW - FORMAT

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U2 - 10.1093/bioinformatics/btac098

DO - 10.1093/bioinformatics/btac098

M3 - RGC 21 - Publication in refereed journal

SN - 1367-4803

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SP - 2333

EP - 2340

JO - Bioinformatics

JF - Bioinformatics

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ER -

mzMD: visualization-oriented MS data storage and retrieval

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GRF: Algorithms for Searching MS Spectra against Protein Databases and Protein Sequencing Using Combined Top-down and Bottom-up Approach for Monoclonal Antibodies

GRF: Efficient Algorithms for Identification of Modified Proteoforms Using Top-down Mass Spectra

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mzMD: visualization-oriented MS data storage and retrieval

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GRF: Algorithms for Searching MS Spectra against Protein Databases and Protein Sequencing Using Combined Top-down and Bottom-up Approach for Monoclonal Antibodies

GRF: Efficient Algorithms for Identification of Modified Proteoforms Using Top-down Mass Spectra

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