TPClust: Temporal Profile-Guided Subtyping Using High-Dimensional Omics Data

Abstract excerpt

Clustering is widely used to identify subtypes in heterogeneous populations, yet most approaches rarely integrate longitudinal phenotypic trajectories with high-dimensional molecular profiles, limiting their ability to resolve biologically and clinically meaningful heterogeneity in progressive diseases. We developed TPClust, a supervised, semi-parametric clustering method that integrates high-dimensional omics dat...

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• Aged
• Alzheimer Disease
• Cluster Analysis
• Clustering Algorithms
• Electronic Health Records
• Longitudinal Studies
• Parkinson Disease
• United Kingdom

Identifiers and source

Literature Corpus work

92b5fb49-9929-5706-b030-c10173341014

DOI

10.1101/2025.08.05.668514