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Creation of libraries of recurring mass spectra from large data sets assisted by a dual-column workflow

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Creation of libraries of recurring mass spectra from large data sets assisted by a dual-column workflow. / Mallard, W. Gary; Andriamaharavo, N. Rabe; Mirokhin, Yuri A.; Halket, John M.; Stein, Stephen E.

In: Analytical Chemistry, Vol. 86, No. 20, 21.10.2014, p. 10231-10238.

Research output: Contribution to journalArticle

Harvard

Mallard, WG, Andriamaharavo, NR, Mirokhin, YA, Halket, JM & Stein, SE 2014, 'Creation of libraries of recurring mass spectra from large data sets assisted by a dual-column workflow', Analytical Chemistry, vol. 86, no. 20, pp. 10231-10238. https://doi.org/10.1021/ac502379x

APA

Mallard, W. G., Andriamaharavo, N. R., Mirokhin, Y. A., Halket, J. M., & Stein, S. E. (2014). Creation of libraries of recurring mass spectra from large data sets assisted by a dual-column workflow. Analytical Chemistry, 86(20), 10231-10238. https://doi.org/10.1021/ac502379x

Vancouver

Mallard WG, Andriamaharavo NR, Mirokhin YA, Halket JM, Stein SE. Creation of libraries of recurring mass spectra from large data sets assisted by a dual-column workflow. Analytical Chemistry. 2014 Oct 21;86(20):10231-10238. https://doi.org/10.1021/ac502379x

Author

Mallard, W. Gary ; Andriamaharavo, N. Rabe ; Mirokhin, Yuri A. ; Halket, John M. ; Stein, Stephen E. / Creation of libraries of recurring mass spectra from large data sets assisted by a dual-column workflow. In: Analytical Chemistry. 2014 ; Vol. 86, No. 20. pp. 10231-10238.

Bibtex Download

@article{85a960c310f54de288f60d2260f37c94,
title = "Creation of libraries of recurring mass spectra from large data sets assisted by a dual-column workflow",
abstract = "An analytical methodology has been developed for extracting recurrent unidentified spectra (RUS) from large GC/MS data sets. Spectra were first extracted from original data files by the Automated Mass Spectral Deconvolution and Identification System (AMDIS; Stein, S. E. J. Am. Soc. Mass Spectrom. 1999, 10, 770-781) using settings designed to minimize spurious spectra, followed by searching the NIST library with all unidentified spectra. The spectra that could not be identified were then filtered to remove poorly deconvoluted data and clustered. The results were assumed to be unidentified components. This was tested by requiring each unidentified spectrum to be found in two chromatographic columns with slightly different stationary phases. This methodology has been applied to a large set of pediatric urine samples. A library of spectra and retention indices for derivatized urine components, both identified and recurrent unidentified, has been created and is available for download.",
author = "Mallard, {W. Gary} and Andriamaharavo, {N. Rabe} and Mirokhin, {Yuri A.} and Halket, {John M.} and Stein, {Stephen E.}",
year = "2014",
month = oct,
day = "21",
doi = "10.1021/ac502379x",
language = "English",
volume = "86",
pages = "10231--10238",
journal = "Analytical Chemistry",
issn = "0003-2700",
publisher = "American Chemical Society",
number = "20",

}

RIS (suitable for import to EndNote) Download

TY - JOUR

T1 - Creation of libraries of recurring mass spectra from large data sets assisted by a dual-column workflow

AU - Mallard, W. Gary

AU - Andriamaharavo, N. Rabe

AU - Mirokhin, Yuri A.

AU - Halket, John M.

AU - Stein, Stephen E.

PY - 2014/10/21

Y1 - 2014/10/21

N2 - An analytical methodology has been developed for extracting recurrent unidentified spectra (RUS) from large GC/MS data sets. Spectra were first extracted from original data files by the Automated Mass Spectral Deconvolution and Identification System (AMDIS; Stein, S. E. J. Am. Soc. Mass Spectrom. 1999, 10, 770-781) using settings designed to minimize spurious spectra, followed by searching the NIST library with all unidentified spectra. The spectra that could not be identified were then filtered to remove poorly deconvoluted data and clustered. The results were assumed to be unidentified components. This was tested by requiring each unidentified spectrum to be found in two chromatographic columns with slightly different stationary phases. This methodology has been applied to a large set of pediatric urine samples. A library of spectra and retention indices for derivatized urine components, both identified and recurrent unidentified, has been created and is available for download.

AB - An analytical methodology has been developed for extracting recurrent unidentified spectra (RUS) from large GC/MS data sets. Spectra were first extracted from original data files by the Automated Mass Spectral Deconvolution and Identification System (AMDIS; Stein, S. E. J. Am. Soc. Mass Spectrom. 1999, 10, 770-781) using settings designed to minimize spurious spectra, followed by searching the NIST library with all unidentified spectra. The spectra that could not be identified were then filtered to remove poorly deconvoluted data and clustered. The results were assumed to be unidentified components. This was tested by requiring each unidentified spectrum to be found in two chromatographic columns with slightly different stationary phases. This methodology has been applied to a large set of pediatric urine samples. A library of spectra and retention indices for derivatized urine components, both identified and recurrent unidentified, has been created and is available for download.

UR - http://www.scopus.com/inward/record.url?scp=84910635318&partnerID=8YFLogxK

U2 - 10.1021/ac502379x

DO - 10.1021/ac502379x

M3 - Article

C2 - 25233296

AN - SCOPUS:84910635318

VL - 86

SP - 10231

EP - 10238

JO - Analytical Chemistry

JF - Analytical Chemistry

SN - 0003-2700

IS - 20

ER -

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