Orthonormal pairwise logratio selection (OPALS) algorithm for compositional data analysis in high dimensions

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F25%3A73631945" target="_blank" >RIV/61989592:15310/25:73631945 - isvavai.cz</a>

Alternative codes found

RIV/61989592:15510/25:73631945

Result on the web

<a href="https://academic.oup.com/bioinformaticsadvances/article/5/1/vbaf229/8270648?login=true" target="_blank" >https://academic.oup.com/bioinformaticsadvances/article/5/1/vbaf229/8270648?login=true</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1093/bioadv/vbaf229" target="_blank" >10.1093/bioadv/vbaf229</a>

Result language

angličtina

Original language name

Orthonormal pairwise logratio selection (OPALS) algorithm for compositional data analysis in high dimensions

Original language description

In the analysis of compositional data, the most fundamental information is conveyed by the pairwise logratios between components. While logratio coordinate representations, such as balances and pivot coordinates, are widely used to aggregate such information into higher-level relationships, there are instances where a fine-grained representation using all pairwise logratios can be advantageous. Performing this within an orthonormal (or orthogonal) logratio coordinate framework becomes particularly challenging for high-dimensional compositions, since a composition with D parts results in pairwise logratios (excluding reciprocals). This work presents an efficient algorithm (OPALS) based on Latin squares theory to obtain all orthonormal pairwise logratios from just logratio coordinate systems. Thus, the computational burden associated with using such representation for data analysis and modelling in high dimensions is notably alleviated, or even made feasible. Moreover, the relationship between estimates from orthonormal pairwise logratios and ordinary pivot coordinates is discussed in the context of regression and classification analysis. The performance and properties of the method are illustrated through two examples using contemporary molecular biology data.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10102 - Applied mathematics

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2025

Confidentiality

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

Name of the periodical

BIOINFORMATICS ADVANCES

ISSN

—

e-ISSN

2635-0041

Volume of the periodical

5

Issue of the periodical within the volume

1

Country of publishing house

GB - UNITED KINGDOM

Number of pages

15

Pages from-to

1-15

UT code for WoS article

001620953800001

EID of the result in the Scopus database

2-s2.0-105022810197