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The software for interactive evaluation of mass spectra stability and reproducibility.
Zhvansky, E S; Sorokin, A A; Bormotov, D S; Bocharov, K V; Zavorotnyuk, D S; Ivanov, D G; Nikolaev, E N; Popov, I A.
Afiliação
  • Zhvansky ES; Phystech School of Biological and Medical Physics, Moscow Institute of Physics and Technology, Moscow, Russia.
  • Sorokin AA; Phystech School of Biological and Medical Physics, Moscow Institute of Physics and Technology, Moscow, Russia.
  • Bormotov DS; Phystech School of Biological and Medical Physics, Moscow Institute of Physics and Technology, Moscow, Russia.
  • Bocharov KV; Phystech School of Biological and Medical Physics, Moscow Institute of Physics and Technology, Moscow, Russia.
  • Zavorotnyuk DS; Phystech School of Biological and Medical Physics, Moscow Institute of Physics and Technology, Moscow, Russia.
  • Ivanov DG; Phystech School of Biological and Medical Physics, Moscow Institute of Physics and Technology, Moscow, Russia.
  • Nikolaev EN; Laboratory of Biomolecular Mass Spectrometry, Emanuel Institute for Biochemical Physics of the Russian Academy of Sciences, Moscow, Russia.
  • Popov IA; Center for Computational and Data-Intensive Science and Engineering, Skolkovo Institute of Science and Technology, Moscow, Russia.
Bioinformatics ; 37(1): 140-142, 2021 Apr 09.
Article em En | MEDLINE | ID: mdl-33367588
ABSTRACT

SUMMARY:

Mass spectrometry (MS) methods are widely used for the analysis of biological and medical samples. Recently developed methods, such as DESI, REIMS and NESI allow fast analyses without sample preparation at the cost of higher variability of spectra. In biology and medicine, MS profiles are often used with machine learning (classification, regression, etc.) algorithms and statistical analysis, which are sensitive to outliers and intraclass variability. Here, we present spectra similarity matrix (SSM) Display software, a tool for fast visual outlier detection and variance estimation in mass spectrometric profiles. The tool speeds up the process of manual spectra inspection, improves accuracy and explainability of outlier detection, and decreases the requirements to the operator experience. It was shown that the batch effect could be revealed through SSM analysis and that the SSM calculation can also be used for tuning novel ion sources concerning the quality of obtained mass spectra. AVAILABILITY AND IMPLEMENTATION Source code, example datasets, binaries and other information are available at https//github.com/EvgenyZhvansky/R_matrix. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2021 Tipo de documento: Article