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Tight Clustering: A Resampling-Based Approach for Identifying Stable and Tight Patterns in Data

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  • George C. Tseng
  • Wing H. Wong

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  • George C. Tseng & Wing H. Wong, 2005. "Tight Clustering: A Resampling-Based Approach for Identifying Stable and Tight Patterns in Data," Biometrics, The International Biometric Society, vol. 61(1), pages 10-16, March.
    • Handle: RePEc:bla:biomet:v:61:y:2005:i:1:p:10-16
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    File URL: http://hdl.handle.net/10.1111/j.0006-341X.2005.031032.x
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    References listed on IDEAS

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    1. McLachlan, G. J. & Peel, D. & Bean, R. W., 2003. "Modelling high-dimensional data by mixtures of factor analyzers," Computational Statistics & Data Analysis, Elsevier, vol. 41(3-4), pages 379-388, January.
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    Cited by:

    1. Liu, Xueli & Lee, Sheng-Chien & Casella, George & Peter, Gary F., 2008. "Assessing agreement of clustering methods with gene expression microarray data," Computational Statistics & Data Analysis, Elsevier, vol. 52(12), pages 5356-5366, August.
    2. Ming Yuan & Christina Kendziorski, 2006. "A Unified Approach for Simultaneous Gene Clustering and Differential Expression Identification," Biometrics, The International Biometric Society, vol. 62(4), pages 1089-1098, December.
    3. Capobianco Enrico & Marras Elisabetta & Travaglione Antonella, 2011. "Multiscale Characterization of Signaling Network Dynamics through Features," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 10(1), pages 1-32, November.
    4. Liang, Faming, 2007. "Use of SVD-based probit transformation in clustering gene expression profiles," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 6355-6366, August.
    5. Segal Mark R. & Xiong Hao & Bengtsson Henrik & Bourgon Richard & Gentleman Robert, 2012. "Querying Genomic Databases: Refining the Connectivity Map," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(2), pages 1-37, January.
    6. Yongsung Joo & George Casella & James Hobert, 2010. "Bayesian model-based tight clustering for time course data," Computational Statistics, Springer, vol. 25(1), pages 17-38, March.
    7. Coffey, N. & Hinde, J. & Holian, E., 2014. "Clustering longitudinal profiles using P-splines and mixed effects models applied to time-course gene expression data," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 14-29.
    8. Zhiguang Huo & Ying Ding & Silvia Liu & Steffi Oesterreich & George Tseng, 2016. "Meta-Analytic Framework for Sparse K -Means to Identify Disease Subtypes in Multiple Transcriptomic Studies," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(513), pages 27-42, March.
    9. Tianzhou Ma & Faming Liang & George C. Tseng, 2017. "Biomarker detection and categorization in ribonucleic acid sequencing meta-analysis using Bayesian hierarchical models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(4), pages 847-867, August.
    10. Hongkai Ji & Wing Hung Wong, 2006. "Computational Biology: Toward Deciphering Gene Regulatory Information in Mammalian Genomes," Biometrics, The International Biometric Society, vol. 62(3), pages 645-663, September.
    11. Gupta, Mayetri, 2014. "An evolutionary Monte Carlo algorithm for Bayesian block clustering of data matrices," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 375-391.
    12. Davide Risso & Liam Purvis & Russell B Fletcher & Diya Das & John Ngai & Sandrine Dudoit & Elizabeth Purdom, 2018. "clusterExperiment and RSEC: A Bioconductor package and framework for clustering of single-cell and other large gene expression datasets," PLOS Computational Biology, Public Library of Science, vol. 14(9), pages 1-16, September.
    13. Yujia Li & Xiangrui Zeng & Chien‐Wei Lin & George C. Tseng, 2022. "Simultaneous estimation of cluster number and feature sparsity in high‐dimensional cluster analysis," Biometrics, The International Biometric Society, vol. 78(2), pages 574-585, June.
    14. Feher Kristen & Whelan James & Müller Samuel, 2011. "Assessing Modularity Using a Random Matrix Theory Approach," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 10(1), pages 1-34, September.
    15. Ranjan Maitra & Ivan P. Ramler, 2009. "Clustering in the Presence of Scatter," Biometrics, The International Biometric Society, vol. 65(2), pages 341-352, June.
    16. He, Yi & Pan, Wei & Lin, Jizhen, 2006. "Cluster analysis using multivariate normal mixture models to detect differential gene expression with microarray data," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 641-658, November.

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