DistSNE: Distributed computing and online visualization of DNA methylation-based central nervous system tumor classification.

ABSTRACT: The current state-of-the-art analysis of central nervous system (CNS) tumors through DNA methylation profiling relies on the tumor classifier developed by Capper and colleagues, which centrally harnesses DNA methylation data provided by users. Here, we present a distributed-computing-based approach for CNS tumor classification that achieves a comparable performance to centralized systems while safeguarding privacy. We utilize the t-distributed neighborhood embedding (t-SNE) model for dimensionality reduction and visualization of tumor classification results in two-dimensional graphs in a distributed approach across multiple sites (DistSNE). DistSNE provides an intuitive web interface (https://gin-tsne.med.uni-giessen.de) for user-friendly local data management and federated methylome-based

SUBMITTER: Schmid K 

PROVIDER: S-EPMC11007060 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature