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Title: 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:
 [1];  [2];  [2];  [1];  [3];  [1];  [1];
  1. Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
  2. Computing and Analytics Division, Pacific Northwest National Laboratory, Richland, WA, USA
  3. 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 Lab. (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. doi: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. doi: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 = {2019},
month = {4}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
DOI: 10.1093/bioinformatics/btz250

Citation Metrics:
Cited by: 7 works
Citation information provided by
Web of Science

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Works referenced in this record:

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