a consensus matrix.
lower bound to define "ambiguous clustering". The value can be a vector.
upper bound to define "ambihuous clustering". The value can be a vector.
percent of extreme values to trim if combinations of
This a variant of the orignial PAC (proportion of ambiguous clustering) method.
PAC_k = F(x_2j) - F(x_1i)
F(x) is the ecdf of the consensus matrix (the lower triangle matrix without diagnals).
The final PAC is the mean of all
PAC_k by removing top
trim/2 percent and bottom
trim/2 percent of all values.
A single numeric score.
See https://www.nature.com/articles/srep06207 for explanation of PAC score.
Zuguang Gu <[email protected]>
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