This method clusters mutations based on the probability that they are from the same distribution. It first computes the zscore associated with a normalized number of alternative reads and depth. The "normalized" number of reads is the number of alternative reads expected if the mutation was at a single copy in a diploid genome.
The classic output from Schrodinger function
returns a list with:
The matrix of probabilities
The dissimilarity matrix
The tree obtained by hierachical clustering of the dissimilarity matrix using "ward.D2" method
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