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mvp - an open-source preprocessor for cleaning duplicate records and missing values in mass spectrometry data.

Geunho Lee1, Hyun Beom Lee2, Byung Hwa Jung2

  • 1School of Electrical Engineering and Computer Science Gwangju Institute of Science and Technology (GIST) Korea.

FEBS Open Bio
|July 7, 2017
PubMed
Summary

This study introduces missing values preprocessor (mvp), an open-source software to clean mass spectrometry (MS) data. mvp effectively reduces duplicate records and missing values, improving data quality for downstream analyses.

Keywords:
MS data preprocessorR packagedirty dataduplicate recordmass spectrometrymissing value

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Area of Science:

  • Analytical Chemistry
  • Bioinformatics
  • Computational Biology

Background:

  • Mass spectrometry (MS) data are crucial for analyzing biological phenomena.
  • MS data frequently suffer from duplicate records and missing values, termed 'dirty data'.
  • Dirty data negatively impacts the performance of statistical and machine-learning analyses.

Purpose of the Study:

  • To develop an open-source software tool for preprocessing mass spectrometry data.
  • To address challenges posed by duplicate records and missing values in MS datasets.
  • To improve the reliability and performance of statistical analyses on MS data.

Main Methods:

  • Developed 'missing values preprocessor' (mvp), an open-source software.
  • Utilized graph theory to form cliques based on MS data properties (mass-to-charge ratio, intensity).
  • Applied mvp to preprocess MS data containing duplicate records and missing values.

Main Results:

  • Quantitative and qualitative analyses validated the effectiveness of the mvp process.
  • mvp successfully reduced issues related to duplicate records and missing values in MS data.
  • Statistical tests using mvp-preprocessed data yielded improved results compared to unprocessed data.

Conclusions:

  • The mvp software provides an effective solution for cleaning mass spectrometry data.
  • Preprocessing MS data with mvp enhances the accuracy and reliability of subsequent statistical analyses.
  • mvp facilitates more robust biological insights from mass spectrometry datasets.