Significance estimation for large scale metabolomics annotations by spectral matching

Matching fragment spectra to reference library spectra is an important procedure for annotating small molecules in untargeted mass spectrometry based metabolomics studies. Here, the authors develop strategies to estimate false discovery rates (FDR) by empirical Bayes and target-decoy based methods w...

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Autores principales:	Kerstin Scheubert, Franziska Hufsky, Daniel Petras, Mingxun Wang, Louis-Félix Nothias, Kai Dührkop, Nuno Bandeira, Pieter C. Dorrestein, Sebastian Böcker
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/ed3d7368472a4d7394ba9f261ba594c4
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spelling	oai:doaj.org-article:ed3d7368472a4d7394ba9f261ba594c42021-12-02T15:38:54ZSignificance estimation for large scale metabolomics annotations by spectral matching10.1038/s41467-017-01318-52041-1723https://doaj.org/article/ed3d7368472a4d7394ba9f261ba594c42017-11-01T00:00:00Zhttps://doi.org/10.1038/s41467-017-01318-5https://doaj.org/toc/2041-1723Matching fragment spectra to reference library spectra is an important procedure for annotating small molecules in untargeted mass spectrometry based metabolomics studies. Here, the authors develop strategies to estimate false discovery rates (FDR) by empirical Bayes and target-decoy based methods which enable a user to define the scoring criteria for spectral matching.Kerstin ScheubertFranziska HufskyDaniel PetrasMingxun WangLouis-Félix NothiasKai DührkopNuno BandeiraPieter C. DorresteinSebastian BöckerNature PortfolioarticleScienceQENNature Communications, Vol 8, Iss 1, Pp 1-10 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Kerstin Scheubert Franziska Hufsky Daniel Petras Mingxun Wang Louis-Félix Nothias Kai Dührkop Nuno Bandeira Pieter C. Dorrestein Sebastian Böcker Significance estimation for large scale metabolomics annotations by spectral matching
description	Matching fragment spectra to reference library spectra is an important procedure for annotating small molecules in untargeted mass spectrometry based metabolomics studies. Here, the authors develop strategies to estimate false discovery rates (FDR) by empirical Bayes and target-decoy based methods which enable a user to define the scoring criteria for spectral matching.
format	article
author	Kerstin Scheubert Franziska Hufsky Daniel Petras Mingxun Wang Louis-Félix Nothias Kai Dührkop Nuno Bandeira Pieter C. Dorrestein Sebastian Böcker
author_facet	Kerstin Scheubert Franziska Hufsky Daniel Petras Mingxun Wang Louis-Félix Nothias Kai Dührkop Nuno Bandeira Pieter C. Dorrestein Sebastian Böcker
author_sort	Kerstin Scheubert
title	Significance estimation for large scale metabolomics annotations by spectral matching
title_short	Significance estimation for large scale metabolomics annotations by spectral matching
title_full	Significance estimation for large scale metabolomics annotations by spectral matching
title_fullStr	Significance estimation for large scale metabolomics annotations by spectral matching
title_full_unstemmed	Significance estimation for large scale metabolomics annotations by spectral matching
title_sort	significance estimation for large scale metabolomics annotations by spectral matching
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/ed3d7368472a4d7394ba9f261ba594c4
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_version_	1718386083375349760

Significance estimation for large scale metabolomics annotations by spectral matching

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