Multi-omics integration with weighted affinity and self-diffusion applied for cancer subtypes identification.

ABSTRACT:

Background

Characterizing cancer molecular subtypes is crucial for improving prognosis and individualized treatment. Integrative analysis of multi-omics data has become an important approach for disease subtyping, yielding better understanding of the complex biology. Current multi-omics integration tools and methods for cancer subtyping often suffer challenges of high computational efficiency as well as the problem of weight assignment on data types.

Results

Here, we present an efficient multi-omics integration via weighted affinity and self-diffusion (MOSD) to dissect cancer heterogeneity. MOSD first construct local scaling affinity on each data type and then integrate all affinities by weighted linear combination, followed by the self-diffusion to further improve the patie

SUBMITTER: Duan X 

PROVIDER: S-EPMC10799401 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature