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<body bgcolor = "#FFFFCC"><basefont face = "Arial"> |
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<h1>KMC: K-Means/K-Medians</h1> <h2> Parameter Information</h2> |
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<hr size = 10> |
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<h2> Sample Selection </h2> |
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The sample selection option indicates whether to cluster genes or experiments. |
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<br> |
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<h2> Distance Metric Selection </h2> |
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This area allows the selection of the metric to be used to assess gene-to-gene |
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or sample-to-sample distances. The initial metric displayed (choosen) corresponds to the global |
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setting in the Multiple Array Viewer's 'Metrics' menu. Alterations to the |
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chosen metric in this dialog will only alter the metric used for the current |
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algorithm run. The global setting in the main 'Metrics' menu will remain unchanged. |
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<br><br> |
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Euclidean Distance and Pearson Correllation tend to be the most frequently used options. |
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An appendix in the MeV manual describes the distance metrics offered in MeV. |
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<br> |
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<h2>Means/Medians option</h2> |
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The Means or Medians option indicates whether each cluster's centroid vector |
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should be calculated a mean or a median of the member expression patterns. |
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<br> |
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<h2> Number of Clusters </h2> |
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This positive integer value indicates the number of clusters to be created. |
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Note that FOM can be used to estimate an appropriate value. |
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<h2> Number of Iterations </h2> |
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This positive integer value is the maximum number of times that all the elements in the data set |
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will be tested for cluster fit. On each iteration each element |
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is associated with the cluster with the closest mean (or median). |
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<br><br> |
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Note that the algorithm will terminate when either no elements |
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require migration (reassignment) to new clusters or when the maximum number of |
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iterations has been reached. |
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<br> |
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<h2> Hierarchical Clustering </h2> |
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This check box selects whether to perform hierarchical clustering on the elements in each cluster |
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created. |
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<br> |
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</basefont> |
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</body> |
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</html> |