CDC STACKS serves as an archival repository of CDC-published products including scientific findings, journal articles, guidelines, recommendations, or other public health information authored or co-authored by CDC or funded partners.
As a repository, CDC STACKS retains documents in their original published format to ensure public access to scientific information.
i
intCC: An efficient weighted integrative consensus clustering of multimodal data
-
2024
-
-
Source: Pac Symp Biocomput. 29:627-640
Details:
-
Alternative Title:Pac Symp Biocomput
-
Personal Author:
-
Description:High throughput profiling of multiomics data provides a valuable resource to better understand the complex human disease such as cancer and to potentially uncover new subtypes. Integrative clustering has emerged as a powerful unsupervised learning framework for subtype discovery. In this paper, we propose an efficient weighted integrative clustering called intCC by combining ensemble method, consensus clustering and kernel learning integrative clustering. We illustrate that intCC can accurately uncover the latent cluster structures via extensive simulation studies and a case study on the TCGA pan cancer datasets. An R package intCC implementing our proposed method is available at https://github.com/candsj/intCC.
-
Keywords:
-
Source:
-
Pubmed ID:38160311
-
Pubmed Central ID:PMC10764072
-
Document Type:
-
Funding:
-
Volume:29
-
Collection(s):
-
Main Document Checksum:
-
Download URL:
-
File Type:
[PDF-1.50 MB]
