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Title: Lipid Mini-On: mining and ontology tool for enrichment analysis of lipidomic data

Journal Article · · Bioinformatics
 [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

Abstract Summary 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. The utility of the tool is demonstrated using biological (e.g. human lung endothelial cells) and environmental (e.g. peat soil) samples. Availability and implementation Rodin (R package: https://github.com/PNNL-Comp-Mass-Spec/Rodin), Lipid Mini-On Shiny app (https://github.com/PNNL-Comp-Mass-Spec/LipidMiniOn) and Lipid Mini-On online tool (https://omicstools.pnnl.gov/shiny/lipid-mini-on/). Supplementary information Supplementary data are available at Bioinformatics online.

Sponsoring Organization:
USDOE
Grant/Contract Number:
AC05-76RL01830
OSTI ID:
1572440
Journal Information:
Bioinformatics, Journal Name: Bioinformatics Journal Issue: 21 Vol. 35; ISSN 1367-4803
Publisher:
Oxford University PressCopyright Statement
Country of Publication:
United Kingdom
Language:
English

References (6)

ggplot2 book January 2016
Cell type-resolved human lung lipidome reveals cellular cooperation in lung function journal September 2018
DOSE: an R/Bioconductor package for disease ontology semantic and enrichment analysis journal October 2014
LIQUID: an-open source software for identifying lipids in LC-MS/MS-based lipidomics data journal January 2017
LMSD: LIPID MAPS structure database journal January 2007
Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists journal November 2008