ArticleThe annals of applied statistics2019
THREE-WAY CLUSTERING OF MULTI-TISSUE MULTI-INDIVIDUAL GENE EXPRESSION DATA USING SEMI-NONNEGATIVE TENSOR DECOMPOSITION.
Article in The annals of applied statistics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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
19 citing papers in PubMed, 39 citations in OpenAlex.
- Assessing tensor decomposition quality of immune profiling data from a dictionary learning perspective.bioRxiv : the preprint server for biology · 2026Article
- Simultaneous clustering and estimation of networks in multiple graphical models.Biostatistics (Oxford, England) · 2025Article
- Flexibility in Gene Coexpression at Developmental and Evolutionary Timescales.Molecular biology and evolution · 2025Article
- Simultaneous acclimation to nitrogen and iron scarcity in open ocean cyanobacteria revealed by sparse tensor decomposition of metatranscriptomes.Science advances · 2025Article
- Optimal variable clustering for high-dimensional matrix valued data.Information and inference : a journal of the IMA · 2025Article
- ebnm: An R Package for Solving the Empirical Bayes Normal Means Problem Using a Variety of Prior Families.Journal of statistical software · 2025Article
- The structure is the message: Preserving experimental context through tensor decomposition.Cell systems · 2024Review
- Multi-way overlapping clustering by Bayesian tensor decomposition.Statistics and its interface · 2024Article
- Bayesian tensor-on-tensor regression with efficient computation.Statistics and its interface · 2024Article
- Comparison of sparse biclustering algorithms for gene expression datasets.Briefings in bioinformatics · 2021Article
- Identification of genes associated with altered gene expression and m6A profiles during hypoxia using tensor decomposition based unsupervised feature extraction.Scientific reports · 2021Article
- Dissect Relationships Between Gene Co-expression and Functional Connectivity in Human Brain.Frontiers in neuroscience · 2021Article
- Evaluating genetic causes of azoospermia: What can we learn from a complex cellular structure and single-cell transcriptomics of the human testis?Human genetics · 2021Review
- Generalized Co-Clustering Analysis via Regularized Alternating Least Squares.Computational statistics & data analysis · 2020Article
- Integrative computational epigenomics to build data-driven gene regulation hypotheses.GigaScience · 2020Article
- THREE-WAY CLUSTERING OF MULTI-TISSUE MULTI-INDIVIDUAL GENE EXPRESSION DATA USING SEMI-NONNEGATIVE TENSOR DECOMPOSITION.The annals of applied statistics · 2019Article
- Optimal Sparse Singular Value Decomposition for High-Dimensional High-Order Data.Journal of the American Statistical Association · 2019Article
- Using SNP Weights Derived From Gene Expression Modules to Improve GWAS Power for Feed Efficiency in Pigs.Frontiers in genetics · 2019Article
- Enter the Matrix: Factorization Uncovers Knowledge from Omics.Trends in genetics : TIG · 2018Review
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
The advent of high-throughput sequencing technologies has led to an increasing availability of large multi-tissue data sets which contain gene expression measurements across different tissues and individuals. In this setting, variation in expression levels arises due to contributions specific to genes, tissues, individuals, and interactions thereof. Classical clustering methods are ill-suited to explore these three-way interactions and struggle to fully extract the insights into transcriptome complexity contained in the data. We propose a new statistical method, called
Indexed as
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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.