Selective pivot logratio coordinates for partial least squares discriminant analysis modelling with applications in metabolomics

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F23%3A73619388" target="_blank" >RIV/61989592:15310/23:73619388 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00098892:_____/23:10157879 RIV/61989592:15640/23:73619388 RIV/61989592:15110/23:73619388

Výsledek na webu

<a href="https://onlinelibrary.wiley.com/doi/10.1002/sta4.592" target="_blank" >https://onlinelibrary.wiley.com/doi/10.1002/sta4.592</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1002/sta4.592" target="_blank" >10.1002/sta4.592</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Selective pivot logratio coordinates for partial least squares discriminant analysis modelling with applications in metabolomics

Popis výsledku v původním jazyce

Data resulting from high-throughput biological experiments are frequently of relative nature. This implies that the most relevant information is on the shape of the data distribution over the biological features more than on the size of the measurements themselves. One well-established way to acknowledge this in statistical processing is through logratio analysis. In the current work, we introduce selective pivot logratio coordinates as a new type of orthonormal logratio coordinate representation for high-dimensional relative (a.k.a. compositional) data. This proposal is aimed to enhance the identification of biomarkers in the context of binary classification problems, which is a common setting of scientific studies in the field. These logratio coordinates are constructed so that the pivot coordinate representing a certain compositional part aggregates all pairwise logratios of that part to the rest but, unlike in the ordinary formulation, excludes those deviating from the main pattern. This novel coordinate system is embedded within a partial least squares discriminant analysis (PLS-DA) model for its practical application. Based on both synthetic and realworld metabolomic data sets, we demonstrate the enhanced performance of the novel approach when compared with other methods used in the area.

Název v anglickém jazyce

Selective pivot logratio coordinates for partial least squares discriminant analysis modelling with applications in metabolomics

Popis výsledku anglicky

Data resulting from high-throughput biological experiments are frequently of relative nature. This implies that the most relevant information is on the shape of the data distribution over the biological features more than on the size of the measurements themselves. One well-established way to acknowledge this in statistical processing is through logratio analysis. In the current work, we introduce selective pivot logratio coordinates as a new type of orthonormal logratio coordinate representation for high-dimensional relative (a.k.a. compositional) data. This proposal is aimed to enhance the identification of biomarkers in the context of binary classification problems, which is a common setting of scientific studies in the field. These logratio coordinates are constructed so that the pivot coordinate representing a certain compositional part aggregates all pairwise logratios of that part to the rest but, unlike in the ordinary formulation, excludes those deviating from the main pattern. This novel coordinate system is embedded within a partial least squares discriminant analysis (PLS-DA) model for its practical application. Based on both synthetic and realworld metabolomic data sets, we demonstrate the enhanced performance of the novel approach when compared with other methods used in the area.

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

10406 - Analytical chemistry

Projekt

<a href="/cs/project/NU20-08-00367" target="_blank" >NU20-08-00367: Nové biomarkery dědičných metabolických poruch</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název periodika

Stat

ISSN

2049-1573

e-ISSN

2049-1573

Svazek periodika

12

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

15

Strana od-do

—

Kód UT WoS článku

001013196600001

EID výsledku v databázi Scopus

2-s2.0-85163695944