ArticleBioinformatics (Oxford, England)2013
Bayesian consensus clustering.
Article in Bioinformatics (Oxford, England), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 151 papers.
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Who cites it
151 citing papers in PubMed.
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- CSIE: cancer subtyping via inference and ensemble.Briefings in bioinformatics · 2026Article
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- Cancer-associated fibroblasts and immune escape-related genes serve as biological markers for the prognosis of colorectal cancer.Hereditas · 2026Article
- Understanding ischemia in children with tuberculous meningitis (iThemba): a protocol paper.BMC pediatrics · 2026Article
- Integrative Analysis of Multimodal Omics Data.Annual review of statistics and its application · 2026Article
- A fast integrative clustering and feature selection approach for high-dimensional multiview data.Statistical methods in medical research · 2026Article
- A Prognostic Risk Model for Hepatocellular Carcinoma Integrating Ferroptosis and Metabolic Reprogramming Signatures.Journal of Cancer · 2026Article
- Characterization and Clinical Diagnostic Potential of IHRDEGs in Renal Interstitial Fibrosis: An Integrative Data Analysis and Model Construction Study.Journal of inflammation research · 2026Article
- Immune-Mitochondrial Crosstalk in Pancreatic Adenocarcinoma: Systematic Identification of Prognostic Biomarkers Through Immune Dictionary FrameworkEndocrine, metabolic & immune disorders drug targets · 2026Article
- Characterization of lactylation-related subtypes and diagnostic markers in myocardial ischemic reperfusion injury using weighted gene coexpression network analysis and machine learning.Frontiers in immunology · 2026Article
- Design, processing, and modeling for longitudinal multiomics microbiome data.Frontiers in cellular and infection microbiology · 2026Review
- Bioinformatic analysis of glycosylation-related genes in intervertebral disc degeneration and their roles in immune infiltration and diagnostic models.Scientific reports · 2025Article
- Semi-supervised Bayesian integration of multiple spatial proteomics datasets.PLoS computational biology · 2025Article
- DSCC: disease subtyping using spectral clustering and community detection from consensus networks.Briefings in bioinformatics · 2025Article
- BAYESIAN LEARNING OF CLINICALLY MEANINGFUL SEPSIS PHENOTYPES IN NORTHERN TANZANIA.The annals of applied statistics · 2025Article
- NETosis Genes and Pathomic Signature: A Novel Prognostic Marker for Ovarian Serous Cystadenocarcinoma.Journal of imaging informatics in medicine · 2025Article
- Retrotransposon methylation profiles and survival in Black women with high-grade serous ovarian carcinoma.Clinical epigenetics · 2025Article
91 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
motivationIn biomedical research a growing number of platforms and technologies are used to measure diverse but related information, and the task of clustering a set of objects based on multiple sources of data arises in several applications. Most current approaches to multisource clustering either independently determine a separate clustering for each data source or determine a single 'joint' clustering for all data sources. There is a need for more flexible approaches that simultaneously model the dependence and the heterogeneity of the data sources.
resultsWe propose an integrative statistical model that permits a separate clustering of the objects for each data source. These separate clusterings adhere loosely to an overall consensus clustering, and hence they are not independent. We describe a computationally scalable Bayesian framework for simultaneous estimation of both the consensus clustering and the source-specific clusterings. We demonstrate that this flexible approach is more robust than joint clustering of all data sources, and is more powerful than clustering each data source independently. We present an application to subtype identification of breast cancer tumor samples using publicly available data from The Cancer Genome Atlas. AVAILABILITY: R code with instructions and examples is available at http://people.duke.edu/%7Eel113/software.html.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.