Lipid Mini-On: mining and ontology tool for enrichment analysis of lipidomic data
Abstract
Here we introduce Lipid Mini-On, an open-source tool that performs lipid enrichment analyses and visualizations of lipidomics data. Lipid Mini-On uses a text-mining process to bin individual lipid names into multiple lipid ontology groups based on the classification (e.g. LipidMaps) and other characteristics, such as chain length. Lipid Mini-On provides users with the capability to conduct enrichment analysis of the lipid ontology terms using a Shiny app with options of five statistical approaches. Lipid classes can be added to customize the user’s database and remain updated as new lipid classes are discovered. Visualization of results is available for all classification options (e.g. lipid subclass and individual fatty acid chains). Results are also visualized through an editable network of relationships between the individual lipids and their associated lipid ontology terms. In conclusion, the utility of the tool is demonstrated using biological (e.g. human lung endothelial cells) and environmental (e.g. peat soil) samples.
- Authors:
-
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
- Computing and Analytics Division, Pacific Northwest National Laboratory, Richland, WA, USA
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, USA, Soil, Water, and Environmental Science Department, Tuscon, AZ, USA
- Publication Date:
- Research Org.:
- Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1572440
- Alternate Identifier(s):
- OSTI ID: 1572976
- Report Number(s):
- PNNL-SA-142630
Journal ID: ISSN 1367-4803
- Grant/Contract Number:
- AC05-76RL01830
- Resource Type:
- Published Article
- Journal Name:
- Bioinformatics
- Additional Journal Information:
- Journal Name: Bioinformatics Journal Volume: 35 Journal Issue: 21; Journal ID: ISSN 1367-4803
- Publisher:
- Oxford University Press
- Country of Publication:
- United Kingdom
- Language:
- English
- Subject:
- 59 BASIC BIOLOGICAL SCIENCES
Citation Formats
Clair, Geremy, Reehl, Sarah, Stratton, Kelly G., Monroe, Matthew E., Tfaily, Malak M., Ansong, Charles, Kyle, Jennifer E., and Kelso, ed., Janet. Lipid Mini-On: mining and ontology tool for enrichment analysis of lipidomic data. United Kingdom: N. p., 2019.
Web. doi:10.1093/bioinformatics/btz250.
Clair, Geremy, Reehl, Sarah, Stratton, Kelly G., Monroe, Matthew E., Tfaily, Malak M., Ansong, Charles, Kyle, Jennifer E., & Kelso, ed., Janet. Lipid Mini-On: mining and ontology tool for enrichment analysis of lipidomic data. United Kingdom. https://doi.org/10.1093/bioinformatics/btz250
Clair, Geremy, Reehl, Sarah, Stratton, Kelly G., Monroe, Matthew E., Tfaily, Malak M., Ansong, Charles, Kyle, Jennifer E., and Kelso, ed., Janet. Fri .
"Lipid Mini-On: mining and ontology tool for enrichment analysis of lipidomic data". United Kingdom. https://doi.org/10.1093/bioinformatics/btz250.
@article{osti_1572440,
title = {Lipid Mini-On: mining and ontology tool for enrichment analysis of lipidomic data},
author = {Clair, Geremy and Reehl, Sarah and Stratton, Kelly G. and Monroe, Matthew E. and Tfaily, Malak M. and Ansong, Charles and Kyle, Jennifer E. and Kelso, ed., Janet},
abstractNote = {Here we introduce Lipid Mini-On, an open-source tool that performs lipid enrichment analyses and visualizations of lipidomics data. Lipid Mini-On uses a text-mining process to bin individual lipid names into multiple lipid ontology groups based on the classification (e.g. LipidMaps) and other characteristics, such as chain length. Lipid Mini-On provides users with the capability to conduct enrichment analysis of the lipid ontology terms using a Shiny app with options of five statistical approaches. Lipid classes can be added to customize the user’s database and remain updated as new lipid classes are discovered. Visualization of results is available for all classification options (e.g. lipid subclass and individual fatty acid chains). Results are also visualized through an editable network of relationships between the individual lipids and their associated lipid ontology terms. In conclusion, the utility of the tool is demonstrated using biological (e.g. human lung endothelial cells) and environmental (e.g. peat soil) samples.},
doi = {10.1093/bioinformatics/btz250},
journal = {Bioinformatics},
number = 21,
volume = 35,
place = {United Kingdom},
year = {Fri Apr 12 00:00:00 EDT 2019},
month = {Fri Apr 12 00:00:00 EDT 2019}
}
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https://doi.org/10.1093/bioinformatics/btz250
https://doi.org/10.1093/bioinformatics/btz250
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Cited by: 28 works
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Works referenced in this record:
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