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MALDIViz : A Comprehensive Informatics Tool for MALDI-MS Data Visualization and Analysis

Jagadeesan, Kishore Kumar LU and Ekström, Simon LU (2017) In SLAS Discovery 22(10). p.1246-1252
Abstract

Recently, mass spectrometry (MS) has emerged as an important tool for high-throughput screening (HTS) providing a direct and label-free detection method, complementing traditional fluorescent and colorimetric methodologies. Among the various MS techniques used for HTS, matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) provides many of the characteristics required for high-throughput analyses, such as low cost, speed, and automation. However, visualization and analysis of the large datasets generated by HTS MALDI-MS can pose significant challenges, especially for multiparametric experiments. The datasets can be generated fast, and the complexity of the experimental data (e.g., screening many different sorbent... (More)

Recently, mass spectrometry (MS) has emerged as an important tool for high-throughput screening (HTS) providing a direct and label-free detection method, complementing traditional fluorescent and colorimetric methodologies. Among the various MS techniques used for HTS, matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) provides many of the characteristics required for high-throughput analyses, such as low cost, speed, and automation. However, visualization and analysis of the large datasets generated by HTS MALDI-MS can pose significant challenges, especially for multiparametric experiments. The datasets can be generated fast, and the complexity of the experimental data (e.g., screening many different sorbent phases, the sorbent mass, and the load, wash, and elution conditions) makes manual data analysis difficult. To address these challenges, a comprehensive informatics tool called MALDIViz was developed. This tool is an R-Shiny-based web application, accessible independently of the operating system and without the need to install any program locally. It has been designed to facilitate easy analysis and visualization of MALDI-MS datasets, comparison of multiplex experiments, and export of the analysis results to high-quality images.

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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
data analysis, data visualization, high-throughput screening, MALDI-MS, proteomics, R
in
SLAS Discovery
volume
22
issue
10
pages
7 pages
publisher
SAGE Publications Inc.
external identifiers
  • scopus:85034739810
  • wos:000415922500009
ISSN
2472-5552
DOI
10.1177/2472555217727517
language
English
LU publication?
yes
id
f11ae0c8-08b1-4977-9a94-56d9fb2a5135
date added to LUP
2017-12-07 13:22:56
date last changed
2018-03-09 03:00:20
@article{f11ae0c8-08b1-4977-9a94-56d9fb2a5135,
  abstract     = {<p>Recently, mass spectrometry (MS) has emerged as an important tool for high-throughput screening (HTS) providing a direct and label-free detection method, complementing traditional fluorescent and colorimetric methodologies. Among the various MS techniques used for HTS, matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) provides many of the characteristics required for high-throughput analyses, such as low cost, speed, and automation. However, visualization and analysis of the large datasets generated by HTS MALDI-MS can pose significant challenges, especially for multiparametric experiments. The datasets can be generated fast, and the complexity of the experimental data (e.g., screening many different sorbent phases, the sorbent mass, and the load, wash, and elution conditions) makes manual data analysis difficult. To address these challenges, a comprehensive informatics tool called MALDIViz was developed. This tool is an R-Shiny-based web application, accessible independently of the operating system and without the need to install any program locally. It has been designed to facilitate easy analysis and visualization of MALDI-MS datasets, comparison of multiplex experiments, and export of the analysis results to high-quality images.</p>},
  author       = {Jagadeesan, Kishore Kumar and Ekström, Simon},
  issn         = {2472-5552},
  keyword      = {data analysis,data visualization,high-throughput screening,MALDI-MS,proteomics,R},
  language     = {eng},
  month        = {12},
  number       = {10},
  pages        = {1246--1252},
  publisher    = {SAGE Publications Inc.},
  series       = {SLAS Discovery},
  title        = {MALDIViz : A Comprehensive Informatics Tool for MALDI-MS Data Visualization and Analysis},
  url          = {http://dx.doi.org/10.1177/2472555217727517},
  volume       = {22},
  year         = {2017},
}