ArticleThe annals of applied statistics2013
SPARSE INTEGRATIVE CLUSTERING OF MULTIPLE OMICS DATA SETS.
Article in The annals of applied statistics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
63 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Statistical genomics in rare cancer.Seminars in cancer biology · 2020Pooled it
- Integrative transcriptomic and experimental analysis identifies GREM1 as a pro-metastatic mediator in lung adenocarcinoma.Journal of translational medicine · 2026Article
- Multivariate Random Forests for Cross-Modal Multi-Omics Integration.bioRxiv : the preprint server for biology · 2026Article
- A fast integrative clustering and feature selection approach for high-dimensional multiview data.Statistical methods in medical research · 2026Article
- A Bayesian Integrative Mixed Modeling Framework for Analysis of the Multi-Site Adolescent Brain and Cognitive Development Study.Data science in science · 2026Article
- Transcriptomic analyses of human brains with Alzheimer's disease identified dysregulated epilepsy-causing genes.Epilepsy & behavior : E&B · 2025Article
- NetMIM: network-based multi-omics integration with block missingness for biomarker selection and disease outcome prediction.Briefings in bioinformatics · 2024Article
- Comparative analysis of integrative classification methods for multi-omics data.Briefings in bioinformatics · 2024Article
- Brain high-throughput multi-omics data reveal molecular heterogeneity in Alzheimer's disease.PLoS biology · 2024Article
- Multi-omics approach for identifying CNV-associated lncRNA signatures with prognostic value in prostate cancer.Non-coding RNA research · 2024Article
- Incorporating graph information in Bayesian factor analysis with robust and adaptive shrinkage priors.Biometrics · 2024Article
- A Bayesian framework for pathway-guided identification of cancer subgroups by integrating multiple types of genomic data.Statistics in medicine · 2023Article
- Bayesian linear mixed model with multiple random effects for prediction analysis on high-dimensional multi-omics data.Bioinformatics (Oxford, England) · 2023Article
- ForestSubtype: a cancer subtype identifying approach based on high-dimensional genomic data and a parallel random forest.BMC bioinformatics · 2023Article
- PENALIZED REGRESSION FOR MULTIPLE TYPES OF MANY FEATURES WITH MISSING DATA.Statistica Sinica · 2023Article
- Transkingdom Network Analysis (TkNA): a systems framework for inferring causal factors underlying host-microbiota and other multi-omic interactions.bioRxiv : the preprint server for biology · 2023Article
- Integrative analysis of multi-omics and imaging data with incorporation of biological information via structural Bayesian factor analysis.Briefings in bioinformatics · 2023Article
- Multi-omics Data Deconvolution and Integration: New Methods, Insights, and Translational Implications.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Statistical Methods for Integrative Clustering of Multi-omics Data.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Bayesian integrative analysis and prediction with application to atherosclerosis cardiovascular disease.Biostatistics (Oxford, England) · 2022Article
3 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
High resolution microarrays and second-generation sequencing platforms are powerful tools to investigate genome-wide alterations in DNA copy number, methylation, and gene expression associated with a disease. An integrated genomic profiling approach measuring multiple omics data types simultaneously in the same set of biological samples would render an integrated data resolution that would not be available with any single data type. In this study, we use penalized latent variable regression methods for joint modeling of multiple omics data types to identify common latent variables that can be used to cluster patient samples into biologically and clinically relevant disease subtypes. We consider lasso (Tibshirani, 1996), elastic net (Zou and Hastie, 2005), and fused lasso (Tibshirani
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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.