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particleMDI: a Julia Package for the Integrative Cluster Analysis of Multiple Datasets

Cunningham, N; Griffin, J; Wild, D; Lee, A; (2019) particleMDI: a Julia Package for the Integrative Cluster Analysis of Multiple Datasets. In: Proceedings of International Conference on Bayesian Statistics in Action BAYSM 2018: Bayesian Statistics and New Generations. (pp. pp. 65-74). Springer, Cham

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Abstract

We present particleMDI, a Julia package for performing integrative cluster analysis on multiple heterogeneous data sets, built within the framework of multiple data integration (MDI). particleMDI updates cluster allocations using a particle Gibbs approach which offers better mixing of the MCMC chain—but at greater computational cost—than the original MDI algorithm. We outline approaches for improving computational performance, finding the potential for greater than an order-of-magnitude improvement. We demonstrate the capability of particleMDI to uncovering the ground truth in simulated and real datasets. All files are available at https://github.com/nathancunn/particleMDI.jl

Type: Proceedings paper
Title: particleMDI: a Julia Package for the Integrative Cluster Analysis of Multiple Datasets
Event: International Conference on Bayesian Statistics in Action BAYSM 2018: Bayesian Statistics and New Generations
Location: University of Warwick, Coventry, UK
Dates: 02 July 2018 - 03 July 2018
DOI: 10.1007/978-3-030-30611-3_7
Publisher version: https://doi.org/10.1007/978-3-030-30611-3_7
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Bayesian inference, Cluster analysis, Computational statistics, Data integration, Particle Monte Carlo methods
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science
URI: https://discovery.ucl.ac.uk/id/eprint/10067900
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