A novel method for subgroup discovery in precision medicine based on topological data analysis.

ABSTRACT:

Background

The Mapper algorithm is a data mining topological tool that can help us to obtain higher level understanding of disease by visualising the structure of patient data as a similarity graph. It has been successfully applied for exploratory analysis of cancer data in the past, delivering several significant subgroup discoveries. Using the Mapper algorithm in practice requires setting up multiple parameters. The graph then needs to be manually analysed according to a research question at hand. It has been highlighted in the literature that Mapper's parameters have significant impact on the output graph shape and there is no established way to select their optimal values. Hence while using the Mapper algorithm, different parameter values and consequently different output graph

SUBMITTER: Loughrey CF 

PROVIDER: S-EPMC11921513 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature