STrenD: Subspace Trend Discovery
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== Procedure == | == Procedure == | ||
| + | 1. Load Tab-delimited txt file. If columns are features and rows are samples, '''File/Load Table'''; If columns are samples and rows are features, '''File/Load Rotated Table'''; | ||
| + | 2. '''Calculate''' for feature clustering and pair-wise neighborhood similarity; | ||
| + | |||
| + | 3. '''Auto selection''' for automatic | ||
== Output files == | == Output files == | ||
Revision as of 16:56, 21 August 2014
Contents |
Software Interface
Procedure
1. Load Tab-delimited txt file. If columns are features and rows are samples, File/Load Table; If columns are samples and rows are features, File/Load Rotated Table;
2. Calculate for feature clustering and pair-wise neighborhood similarity;
3. Auto selection for automatic
Output files
Input: 17 samples of 3196 dimensions, clustering sigma = 0.8, k = 4:
1. 3196_17_0.8_clustering.txt: agglomerative clustering result, containing index and feature names;
2. 3196_17_0.8_4_NS.txt: pair-wise neighborhood similarity matrix of feature clusters;
3. Shanbhag.txt: intermediate outputs for Shanbhag thresholding;
4. 3196_17_0.8_4_AutoSelFeatures.txt: selected feature index and names;
5. data_selected_vis.txt: table of normalized data with selected features for visualization;
6. vis_coordinates.txt: output coordinates for visualization after dimension reduction by t-SNE.
