Supervised semi-automated data analysis software for gas chromatography / differential mobility spectrometry (GC/DMS) metabolomics applications

Daniel J. Peirano, Alberto Pasamontes, Cristina E Davis

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Modern differential mobility spectrometers (DMS) produce complex and multi-dimensional data streams that allow for near-real-time or post-hoc chemical detection for a variety of applications. An active area of interest for this technology is metabolite monitoring for biological applications, and these data sets regularly have unique technical and data analysis end user requirements. While there are initial publications on how investigators have individually processed and analyzed their DMS metabolomic data, there are no user-ready commercial or open source software packages that are easily used for this purpose. We have created custom software uniquely suited to analyze gas chromatograph / differential mobility spectrometry (GC/DMS) data from biological sources. Here we explain the implementation of the software, describe the user features that are available, and provide an example of how this software functions using a previously-published data set. The software is compatible with many commercial or home-made DMS systems. Because the software is versatile, it can also potentially be used for other similarly structured data sets, such as GC/GC and other IMS modalities.

Original languageEnglish (US)
Pages (from-to)155-166
Number of pages12
JournalInternational Journal for Ion Mobility Spectrometry
Volume19
Issue number2-3
DOIs
StatePublished - Sep 1 2016

Fingerprint

Gas chromatography
Spectrometry
Spectrometers
Chemical detection
Metabolites
Software packages
Gases
Monitoring
Metabolomics
Open source software

Keywords

  • Data analysis
  • Differential mobility spectrometry (DMS)
  • Field asymmetric ion mobility spectrometry (FAIMS)
  • Partial least squares regression (PLS)
  • Principal component analysis (PCA)
  • Software

ASJC Scopus subject areas

  • Spectroscopy

Cite this

Supervised semi-automated data analysis software for gas chromatography / differential mobility spectrometry (GC/DMS) metabolomics applications. / Peirano, Daniel J.; Pasamontes, Alberto; Davis, Cristina E.

In: International Journal for Ion Mobility Spectrometry, Vol. 19, No. 2-3, 01.09.2016, p. 155-166.

Research output: Contribution to journalArticle

@article{2db4e3b96920466eae5cea7ae59f3813,
title = "Supervised semi-automated data analysis software for gas chromatography / differential mobility spectrometry (GC/DMS) metabolomics applications",
abstract = "Modern differential mobility spectrometers (DMS) produce complex and multi-dimensional data streams that allow for near-real-time or post-hoc chemical detection for a variety of applications. An active area of interest for this technology is metabolite monitoring for biological applications, and these data sets regularly have unique technical and data analysis end user requirements. While there are initial publications on how investigators have individually processed and analyzed their DMS metabolomic data, there are no user-ready commercial or open source software packages that are easily used for this purpose. We have created custom software uniquely suited to analyze gas chromatograph / differential mobility spectrometry (GC/DMS) data from biological sources. Here we explain the implementation of the software, describe the user features that are available, and provide an example of how this software functions using a previously-published data set. The software is compatible with many commercial or home-made DMS systems. Because the software is versatile, it can also potentially be used for other similarly structured data sets, such as GC/GC and other IMS modalities.",
keywords = "Data analysis, Differential mobility spectrometry (DMS), Field asymmetric ion mobility spectrometry (FAIMS), Partial least squares regression (PLS), Principal component analysis (PCA), Software",
author = "Peirano, {Daniel J.} and Alberto Pasamontes and Davis, {Cristina E}",
year = "2016",
month = "9",
day = "1",
doi = "10.1007/s12127-016-0200-9",
language = "English (US)",
volume = "19",
pages = "155--166",
journal = "International Journal for Ion Mobility Spectrometry",
issn = "1435-6163",
publisher = "Springer Verlag",
number = "2-3",

}

TY - JOUR

T1 - Supervised semi-automated data analysis software for gas chromatography / differential mobility spectrometry (GC/DMS) metabolomics applications

AU - Peirano, Daniel J.

AU - Pasamontes, Alberto

AU - Davis, Cristina E

PY - 2016/9/1

Y1 - 2016/9/1

N2 - Modern differential mobility spectrometers (DMS) produce complex and multi-dimensional data streams that allow for near-real-time or post-hoc chemical detection for a variety of applications. An active area of interest for this technology is metabolite monitoring for biological applications, and these data sets regularly have unique technical and data analysis end user requirements. While there are initial publications on how investigators have individually processed and analyzed their DMS metabolomic data, there are no user-ready commercial or open source software packages that are easily used for this purpose. We have created custom software uniquely suited to analyze gas chromatograph / differential mobility spectrometry (GC/DMS) data from biological sources. Here we explain the implementation of the software, describe the user features that are available, and provide an example of how this software functions using a previously-published data set. The software is compatible with many commercial or home-made DMS systems. Because the software is versatile, it can also potentially be used for other similarly structured data sets, such as GC/GC and other IMS modalities.

AB - Modern differential mobility spectrometers (DMS) produce complex and multi-dimensional data streams that allow for near-real-time or post-hoc chemical detection for a variety of applications. An active area of interest for this technology is metabolite monitoring for biological applications, and these data sets regularly have unique technical and data analysis end user requirements. While there are initial publications on how investigators have individually processed and analyzed their DMS metabolomic data, there are no user-ready commercial or open source software packages that are easily used for this purpose. We have created custom software uniquely suited to analyze gas chromatograph / differential mobility spectrometry (GC/DMS) data from biological sources. Here we explain the implementation of the software, describe the user features that are available, and provide an example of how this software functions using a previously-published data set. The software is compatible with many commercial or home-made DMS systems. Because the software is versatile, it can also potentially be used for other similarly structured data sets, such as GC/GC and other IMS modalities.

KW - Data analysis

KW - Differential mobility spectrometry (DMS)

KW - Field asymmetric ion mobility spectrometry (FAIMS)

KW - Partial least squares regression (PLS)

KW - Principal component analysis (PCA)

KW - Software

UR - http://www.scopus.com/inward/record.url?scp=84969816031&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84969816031&partnerID=8YFLogxK

U2 - 10.1007/s12127-016-0200-9

DO - 10.1007/s12127-016-0200-9

M3 - Article

VL - 19

SP - 155

EP - 166

JO - International Journal for Ion Mobility Spectrometry

JF - International Journal for Ion Mobility Spectrometry

SN - 1435-6163

IS - 2-3

ER -