Fahy, Eoin, Alvarez-Jarreta, Jorge, Brasher, Christopher J., Nguyen, An, Hawksworth, Jade I., Rodrigues, Patricia ORCID: https://orcid.org/0000-0003-0768-0013, Meckelmann, Sven, Allen, Stuart M. ORCID: https://orcid.org/0000-0003-1776-7489 and O'Donnell, Valerie B. ORCID: https://orcid.org/0000-0003-4089-8460 2019. LipidFinder on LIPID MAPS: peak filtering, MS searching and statistical analysis for lipidomics. Bioinformatics 35 (4) , pp. 685-687. 10.1093/bioinformatics/bty679 |
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Abstract
Summary We present LipidFinder online, hosted on the LIPID MAPS website, as a liquid chromatography/mass spectrometry (LC/MS) workflow comprising peak filtering, MS searching and statistical analysis components, highly customized for interrogating lipidomic data. The online interface of LipidFinder includes several innovations such as comprehensive parameter tuning, a MS search engine employing in-house customized, curated and computationally generated databases and multiple reporting/display options. A set of integrated statistical analysis tools which enable users to identify those features which are significantly-altered under the selected experimental conditions, thereby greatly reducing the complexity of the peaklist prior to MS searching is included. LipidFinder is presented as a highly flexible, extensible user-friendly online workflow which leverages the lipidomics knowledge base and resources of the LIPID MAPS website, long recognized as a leading global lipidomics portal.
Item Type: | Article |
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Date Type: | Publication |
Status: | Published |
Schools: | Medicine Computer Science & Informatics |
Additional Information: | This is an open access article distributed under the terms of the Creative Commons CC BY license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
Publisher: | Oxford University Press |
ISSN: | 1367-4803 |
Funders: | Wellcome Trust |
Date of First Compliant Deposit: | 3 September 2018 |
Date of Acceptance: | 6 August 2018 |
Last Modified: | 11 Oct 2023 18:52 |
URI: | https://orca.cardiff.ac.uk/id/eprint/114547 |
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