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EXPLANA: A user-friendly workflow for EXPLoratory ANAlysis and feature selection in cross-sectional and longitudinal microbiome studies.
Fouquier, Jennifer; Stanislawski, Maggie; O'Connor, John; Scadden, Ashley; Lozupone, Catherine.
Afiliación
  • Fouquier J; Department of Biomedical Informatics, School of Medicine, University of Colorado, Anschutz Medical Campus, Aurora, CO.
  • Stanislawski M; Department of Biomedical Informatics, School of Medicine, University of Colorado, Anschutz Medical Campus, Aurora, CO.
  • O'Connor J; Department of Biomedical Informatics, School of Medicine, University of Colorado, Anschutz Medical Campus, Aurora, CO.
  • Scadden A; Department of Biomedical Informatics, School of Medicine, University of Colorado, Anschutz Medical Campus, Aurora, CO.
  • Lozupone C; Department of Biomedical Informatics, School of Medicine, University of Colorado, Anschutz Medical Campus, Aurora, CO.
bioRxiv ; 2024 Aug 15.
Article en En | MEDLINE | ID: mdl-39185201
ABSTRACT
Motivation Longitudinal microbiome studies (LMS) are increasingly common but have analytic challenges including non-independent data requiring mixed-effects models and large amounts of data that motivate exploratory analysis to identify factors related to outcome variables. Although change analysis (i.e. calculating deltas between values at different timepoints) can be powerful, how to best conduct these analyses is not always clear. For example, observational LMS measurements show natural fluctuations, so baseline might not be a reference of primary interest; whereas, for interventional LMS, baseline is a key reference point, often indicating the start of treatment.

Results:

To address these challenges, we developed a feature selection workflow for cross-sectional and LMS that supports numerical and categorical data called EXPLANA (EXPLoratory ANAlysis). Machine-learning methods were combined with different types of change calculations and downstream interpretation methods to identify statistically meaningful variables and explain their relationship to outcomes. EXPLANA generates an interactive report that textually and graphically summarizes methods and results. EXPLANA had good performance on simulated data, with an average area under the curve (AUC) of 0.91 (range 0.79-1.0, SD = 0.05), outperformed an existing tool (AUC 0.95 vs. 0.56), and identified novel order-dependent categorical feature changes. EXPLANA is broadly applicable and simplifies analytics for identifying features related to outcomes of interest.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: BioRxiv Año: 2024 Tipo del documento: Article Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: BioRxiv Año: 2024 Tipo del documento: Article Pais de publicación: Estados Unidos