Trustworthiness and metrics in visualizing similarity of gene expression

  title={Trustworthiness and metrics in visualizing similarity of gene expression},
  author={Samuel Kaski and Janne Nikkil{\"a} and Merja Oja and Jarkko Venna and Petri T{\"o}r{\"o}nen and Eero Castr{\'e}n},
  journal={BMC Bioinformatics},
  pages={48 - 48}
Conventionally, the first step in analyzing the large and high-dimensional data sets measured by microarrays is visual exploration. Dendrograms of hierarchical clustering, self-organizing maps (SOMs), and multidimensional scaling have been used to visualize similarity relationships of data samples. We address two central properties of the methods: (i) Are the visualizations trustworthy, i.e., if two samples are visualized to be similar, are they really similar? (ii) The metric. The measure of… CONTINUE READING
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Exploratory clustering of gene expression profiles of mutated yeast strains

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