LORA, Lipid Over-Representation Analysis Based on Structural Information

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985823%3A_____%2F23%3A00575776" target="_blank" >RIV/67985823:_____/23:00575776 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1021/acs.analchem.3c02039" target="_blank" >https://doi.org/10.1021/acs.analchem.3c02039</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1021/acs.analchem.3c02039" target="_blank" >10.1021/acs.analchem.3c02039</a>

Jazyk výsledku

angličtina

Název v původním jazyce

LORA, Lipid Over-Representation Analysis Based on Structural Information

Popis výsledku v původním jazyce

With the increasing number of lipidomic studies, there is a need for an efficient and automated analysis of lipidomic data. One of the challenges faced by most existing approaches to lipidomic data analysis is lipid nomenclature. The systematic nomenclature of lipids contains all available information about the molecule, including its hierarchical representation, which can be used for statistical evaluation. The Lipid Over-Representation Analysis (LORA) web application (https://lora.metabolomics.fgu.cas.cz) analyzes this information using the Java-based Goslin framework, which translates lipid names into a standardized nomenclature. Goslin provides the level of lipid hierarchy, including information on headgroups, acyl chains, and their modifications, up to the “complete structure” level. LORA allows the user to upload the experimental query and reference data sets, select a grammar for lipid name normalization, and then process the data. The user can then interactively explore the results and perform lipid over-representation analysis based on selected criteria. The results are graphically visualized according to the lipidome hierarchy. The lipids present in the most over-represented terms (lipids with the highest number of enriched shared structural features) are defined as Very Important Lipids (VILs). For example, the main result of a demo data set is the information that the query is significantly enriched with “glycerophospholipids” containing “acyl 20:4” at the “sn-2 position”. These terms define a set of VILs (e.g., PC 18:2/20:4,O and PE 16:0/20:4(5,8,10,14),OH). All results, graphs, and visualizations are summarized in a report. LORA is a tool focused on the smart mining of epilipidomics data sets to facilitate their interpretation at the molecular level.

Název v anglickém jazyce

LORA, Lipid Over-Representation Analysis Based on Structural Information

Popis výsledku anglicky

With the increasing number of lipidomic studies, there is a need for an efficient and automated analysis of lipidomic data. One of the challenges faced by most existing approaches to lipidomic data analysis is lipid nomenclature. The systematic nomenclature of lipids contains all available information about the molecule, including its hierarchical representation, which can be used for statistical evaluation. The Lipid Over-Representation Analysis (LORA) web application (https://lora.metabolomics.fgu.cas.cz) analyzes this information using the Java-based Goslin framework, which translates lipid names into a standardized nomenclature. Goslin provides the level of lipid hierarchy, including information on headgroups, acyl chains, and their modifications, up to the “complete structure” level. LORA allows the user to upload the experimental query and reference data sets, select a grammar for lipid name normalization, and then process the data. The user can then interactively explore the results and perform lipid over-representation analysis based on selected criteria. The results are graphically visualized according to the lipidome hierarchy. The lipids present in the most over-represented terms (lipids with the highest number of enriched shared structural features) are defined as Very Important Lipids (VILs). For example, the main result of a demo data set is the information that the query is significantly enriched with “glycerophospholipids” containing “acyl 20:4” at the “sn-2 position”. These terms define a set of VILs (e.g., PC 18:2/20:4,O and PE 16:0/20:4(5,8,10,14),OH). All results, graphs, and visualizations are summarized in a report. LORA is a tool focused on the smart mining of epilipidomics data sets to facilitate their interpretation at the molecular level.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10406 - Analytical chemistry

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Analytical Chemistry

ISSN

0003-2700

e-ISSN

1520-6882

Svazek periodika

95

Číslo periodika v rámci svazku

34

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

5

Strana od-do

12600-12604

Kód UT WoS článku

001049424800001

EID výsledku v databázi Scopus

2-s2.0-85169040859