BATL: Bayesian annotations for targeted lipidomics
| Autor: | Justin G. Chitpin, Anuradha Surendra, Thao T. Nguyen, Graeme P. Taylor, Hongbin Xu, Irina Alecu, Roberto Ortega, Julianna J. Tomlinson, Angela M. Crawley, Michaeline McGuinty, Michael G. Schlossmacher, Rachel Saunders-Pullman, Miroslava Cuperlovic-Culf, Steffany A.L. Bennett, Theodore J. Perkins |
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| Přispěvatelé: | Vitek, Olga |
| Rok vydání: | 2021 |
| Předmět: |
Statistics and Probability
0303 health sciences Computer science business.industry Bayesian probability Posterior probability Pattern recognition Biochemistry Computer Science Applications Naive Bayes classifier Identification (information) 03 medical and health sciences Computational Mathematics Software 0302 clinical medicine Computational Theory and Mathematics Lipidomics Artificial intelligence business Retention time Molecular Biology 030217 neurology & neurosurgery 030304 developmental biology |
| Zdroj: | Bioinformatics. 38:1593-1599 |
| ISSN: | 1367-4811 1367-4803 |
| Popis: | Motivation Bioinformatic tools capable of annotating, rapidly and reproducibly, large, targeted lipidomic datasets are limited. Specifically, few programs enable high-throughput peak assessment of liquid chromatography–electrospray ionization tandem mass spectrometry data acquired in either selected or multiple reaction monitoring modes. Results We present here Bayesian Annotations for Targeted Lipidomics, a Gaussian naïve Bayes classifier for targeted lipidomics that annotates peak identities according to eight features related to retention time, intensity, and peak shape. Lipid identification is achieved by modeling distributions of these eight input features across biological conditions and maximizing the joint posterior probabilities of all peak identities at a given transition. When applied to sphingolipid and glycerophosphocholine selected reaction monitoring datasets, we demonstrate over 95% of all peaks are rapidly and correctly identified. Availability and implementation BATL software is freely accessible online at https://complimet.ca/batl/ and is compatible with Safari, Firefox, Chrome and Edge. Supplementary information Supplementary data are available at Bioinformatics online. |
| Databáze: | OpenAIRE |
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