Exploratory consensus of hierarchical clusterings for melanoma and breast cancer.

  title={Exploratory consensus of hierarchical clusterings for melanoma and breast cancer.},
  author={Pritha Mahata},
  journal={IEEE/ACM transactions on computational biology and bioinformatics},
  volume={7 1},
Finding subtypes of heterogeneous diseases is the biggest challenge in the area of biology. Often, clustering is used to provide a hypothesis for the subtypes of a heterogeneous disease. However, there are usually discrepancies between the clusterings produced by different algorithms. This work introduces a simple method which provides the most consistent clusters across three different clustering algorithms for a melanoma and a breast cancer data set. The method is validated by showing that… CONTINUE READING
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