STrenD: Subspace Trend Discovery
Contents |
Clustering
Clustering is for data dimension deduction to speed up the analysis and to achieve better progression tree. Clustering is available in both sample/feature space, and only feature clustering based on their correlation is needed now.
For feature cluster, besides "Feature Coherence", "Feature Merge Coherence" is the Pearson correlation coefficient of two clustered modules, if the correlation coeffient of two modules exceeds the merge coherence, these two modules will be merged. Its arrange is also 0-1. Click Feature cluster for feature clustering.
Recommended param setting:
Feature clustering: coherence = 0.95 or higher for small feature size, 0.7 for large feature size; merge coherence = 0.9.
Overall Progression or Progression over Distance
If the checkbox Progression over distance to device is checked, the analysis is for progression over distance rather than overall progression. This is available only when distance to device has been calculated in TraceEditor.
Module Matching
Instead of previous MST/EMD module matching, a correlation-based module matching is adopted for large sample size. A similarity matrix of the feature modules will be generated by clicking Match.
Select Similar Modules
Once the modules matching finished, PSM(progression similarity matrix) threshold is set to determine whether two modules are similar. "PSM Selected Blocks' Percentage" is the percentage of the selected values in the similarity matrix higher than the threshold. If you want to select fewer feature modules, then set the threshold higher and percentage would drop correspondingly as fewer values are above the threshold. Click Show PSM, a heatmap window would show up for you to select the similar modules. The heatmap is colored from red to blue, representing high similarity to low similarity. It's symetric so it's recommended to select along the diagonal by left button down clicking on the block where you want to start and left button up clicking on the block where you want to end. All the blocks in this symmetric square will be chosen and their corresponding feature module IDs will be filled in the "Input hand-picked modules". You would also input or delete any feature module by hand, please notice that all the feature module ID should be separated by comma.
Recommended param setting for :
Overall progression: Set the threshold so that the percentage is around 0.3.
Progression over distance to device: Sometimes the PSM threshold must be low enough to guarantee some modules are selected.
Threshold Heatmap and Progression Tree
After the selected modules are all set, click View Progression, the threshold heatmap is built. By right clicking to make a cut line across the dendrogram of the samples on the left side of the heatmap, the progression tree is built. Each node represents a cluster by the cut. You can select the nodes and view the corresponding items in other views. If you have loaded two kinds of traces all at once in the Trace Editor, say device traces and control trace, "Id to separate" is to tell them apart according to the "Root Trace" in "Computed Features for Cells", the first percentage in the tree label would tell the percentage of the cells from the first data(ID below "Id to separate")( They won't show up if all of them is 100%). The second percentage in the tree label tells how much percentage of the cells are within the distance of "700" near the device( They won't show up if the distance is not available).
Progression Heatmap and Scatter Plot
By clicking "Heatmap", You can furtherly arrange the clusters in the progression tree order and check each feature over the progression in the scatter plot.
