Generate perturbated counts from the original counts by the Poisson distribution.
perturbate_poisson(counts, strength = 1)
The original counts. The rows and columns correspond to samples and features. The values are count of features.
How much perturbated.
0.0 is weak.
1.0 is strong.
A perturbated counts as a
matrix. The matrix's counts are
perturbated from the original counts. The shape of the matrix is
the same as the original counts. The dimension names of the
matrix are also the same as the original counts.
This is an API for advanced users. This API may be changed.