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A cool feature to add to the package would be a consensus heatmap to visualize the consensus matrix, and you could add a covariate bar for cluster assignments.
For example, something similar to this (example from the cola R package):
so the main heatmap would show the consensus probabilities for all pairs of subjects (high is blue, low is white)
Then you can add a covariate bar for the cluster assignments (see the "Class" bar on the left, you can ignore the other bars)
Ideally, you want to see diagonal dark blue boxes corresponding to the number of clusters, and the off-diagonals should be white
Then it would be really cool to be able to make the heatmap for a different number of cluster assignments (e.g. ranging the total number of clusters from 2 to 6), like here:
Unlike cola, the consensus matrix for IMPACC will be the same for all K, but nevertheless it would still be cool to add the cluster-assignments for varying K to the heatmap. Then maybe such plots could help the user select the best value of K.
You might need to sort the consensus matrix in a clever way for a given value of K (e.g. sort patients by cluster assignment, for example) in order to see the clustering patterns better
The text was updated successfully, but these errors were encountered:
A cool feature to add to the package would be a consensus heatmap to visualize the consensus matrix, and you could add a covariate bar for cluster assignments.
For example, something similar to this (example from the cola R package):
Then it would be really cool to be able to make the heatmap for a different number of cluster assignments (e.g. ranging the total number of clusters from 2 to 6), like here:
cola
, the consensus matrix for IMPACC will be the same for all K, but nevertheless it would still be cool to add the cluster-assignments for varying K to the heatmap. Then maybe such plots could help the user select the best value of K.The text was updated successfully, but these errors were encountered: