Bayesian nonparametric clustering for large data sets

  • Daiane Aparecida Zuanetti
  • Peter Müller
  • Yitan Zhu
  • Shengjie Yang
  • Yuan Ji
Article
  • 20 Downloads

Abstract

We propose two nonparametric Bayesian methods to cluster big data and apply them to cluster genes by patterns of gene–gene interaction. Both approaches define model-based clustering with nonparametric Bayesian priors and include an implementation that remains feasible for big data. The first method is based on a predictive recursion which requires a single cycle (or few cycles) of simple deterministic calculations for each observation under study. The second scheme is an exact method that divides the data into smaller subsamples and involves local partitions that can be determined in parallel. In a second step, the method requires only the sufficient statistics of each of these local clusters to derive global clusters. Under simulated and benchmark data sets the proposed methods compare favorably with other clustering algorithms, including k-means, DP-means, DBSCAN, SUGS, streaming variational Bayes and an EM algorithm. We apply the proposed approaches to cluster a large data set of gene–gene interactions extracted from the online search tool “Zodiac.”

Keywords

Big data clustering Gene–gene interactions Predictive recursion Nonparametric Bayes TCGA 

Notes

Acknowledgements

D. Zuanetti was supported by CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brazil. Peter Müller and Yuan Ji are supported in part by NIH/NCI CA 132891-07.

Supplementary material

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Supplementary material 1 (R 9 KB)
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Supplementary material 2 (R 16 KB)
11222_2018_9803_MOESM3_ESM.pdf (120 kb)
Supplementary material 3 (pdf 119 KB)

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Departamento de EstatísticaUniversidade Federal de São CarlosSão CarlosBrazil
  2. 2.Department of MathematicsUT AustinAustinUSA
  3. 3.NorthShore University HealthSystemEvanstonUSA
  4. 4.NorthShore University HealthSystem, Evanston and University of ChicagoEvanstonUSA

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