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bioRxiv · 10.1101/228551

polyCluster: Defining Communities of Reconciled Cancer Subtypes with Biological and Prognostic Significance

Eason, K.·Nyamundanda, G.·Sadanandam, A.
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Abstract

To stratify cancer patients for most beneficial therapies, it is a priority to define robust molecular subtypes using clustering methods and \"big data\". If each of these methods produces different numbers of clusters for the same data, it is difficult to achieve an optimal solution. Here, we introduce \"polyCluster\", a tool that reconciles clusters identified by different methods into context-specific subtype \"communities\" using a hypergeometric test or a measure of relative proportion of common samples. The polycluster was tested using a breast cancer dataset, and latter using uveal melanoma datasets to identify novel subtype communities with significant metastasis-free prognostic differences. Available at: https://github.com/syspremed/polyClustR

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Eason, K., Nyamundanda, G., Sadanandam, A.. 2017-12-04. polyCluster: Defining Communities of Reconciled Cancer Subtypes with Biological and Prognostic Significance. https://doi.org/10.1101/228551

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