Generate perturbated counts from the original counts by the Poisson distribution.

perturbate_poisson(counts, strength = 1)

Arguments

counts

The original counts. The rows and columns correspond to samples and features. The values are count of features.

strength

How much perturbated. 0.0 is weak. 1.0 is strong.

Value

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.

Note

This is an API for advanced users. This API may be changed.