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QSRR Automator: A Tool for Automating Retention Time Prediction in Lipidomics and Metabolomics
The use of retention time is often critical for the identification of compounds in metabolomic and lipidomic studies. Standards are frequently unavailable for the retention time measurement of many metabolites, thus the ability to predict retention time for these compounds is highly valuable. A numb...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7345697/ https://www.ncbi.nlm.nih.gov/pubmed/32526851 http://dx.doi.org/10.3390/metabo10060237 |
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author | Naylor, Bradley C. Catrow, J. Leon Maschek, J. Alan Cox, James E. |
author_facet | Naylor, Bradley C. Catrow, J. Leon Maschek, J. Alan Cox, James E. |
author_sort | Naylor, Bradley C. |
collection | PubMed |
description | The use of retention time is often critical for the identification of compounds in metabolomic and lipidomic studies. Standards are frequently unavailable for the retention time measurement of many metabolites, thus the ability to predict retention time for these compounds is highly valuable. A number of studies have applied machine learning to predict retention times, but applying a published machine learning model to different lab conditions is difficult. This is due to variation between chromatographic equipment, methods, and columns used for analysis. Recreating a machine learning model is likewise difficult without a dedicated bioinformatician. Herein we present QSRR Automator, a software package to automate retention time prediction model creation and demonstrate its utility by testing data from multiple chromatography columns from previous publications and in-house work. Analysis of these data sets shows similar accuracy to published models, demonstrating the software’s utility in metabolomic and lipidomic studies. |
format | Online Article Text |
id | pubmed-7345697 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-73456972020-07-09 QSRR Automator: A Tool for Automating Retention Time Prediction in Lipidomics and Metabolomics Naylor, Bradley C. Catrow, J. Leon Maschek, J. Alan Cox, James E. Metabolites Article The use of retention time is often critical for the identification of compounds in metabolomic and lipidomic studies. Standards are frequently unavailable for the retention time measurement of many metabolites, thus the ability to predict retention time for these compounds is highly valuable. A number of studies have applied machine learning to predict retention times, but applying a published machine learning model to different lab conditions is difficult. This is due to variation between chromatographic equipment, methods, and columns used for analysis. Recreating a machine learning model is likewise difficult without a dedicated bioinformatician. Herein we present QSRR Automator, a software package to automate retention time prediction model creation and demonstrate its utility by testing data from multiple chromatography columns from previous publications and in-house work. Analysis of these data sets shows similar accuracy to published models, demonstrating the software’s utility in metabolomic and lipidomic studies. MDPI 2020-06-09 /pmc/articles/PMC7345697/ /pubmed/32526851 http://dx.doi.org/10.3390/metabo10060237 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Naylor, Bradley C. Catrow, J. Leon Maschek, J. Alan Cox, James E. QSRR Automator: A Tool for Automating Retention Time Prediction in Lipidomics and Metabolomics |
title | QSRR Automator: A Tool for Automating Retention Time Prediction in Lipidomics and Metabolomics |
title_full | QSRR Automator: A Tool for Automating Retention Time Prediction in Lipidomics and Metabolomics |
title_fullStr | QSRR Automator: A Tool for Automating Retention Time Prediction in Lipidomics and Metabolomics |
title_full_unstemmed | QSRR Automator: A Tool for Automating Retention Time Prediction in Lipidomics and Metabolomics |
title_short | QSRR Automator: A Tool for Automating Retention Time Prediction in Lipidomics and Metabolomics |
title_sort | qsrr automator: a tool for automating retention time prediction in lipidomics and metabolomics |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7345697/ https://www.ncbi.nlm.nih.gov/pubmed/32526851 http://dx.doi.org/10.3390/metabo10060237 |
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