# cellrank.external.kernels.WOTKernel.compute_initial_growth_rates

WOTKernel.compute_initial_growth_rates(proliferation_key=None, apoptosis_key=None, organism=None, beta_min=0.3, beta_max=1.7, delta_min=0.3, delta_max=1.7, key_added=None, **kwargs)[source]

Estimate initial growth rates using a birth-death process as described in .

The doubling time is defined as $$\frac{\ln 2}{\beta - \delta}$$ (similarly defined for half-time). The logistic function is used to transform the birth/death rate scores and to smoothly interpolate between specified minimum and maximum birth/death rates.

Parameters
Return type
Returns

pandas.Series The estimated initial growth rates if key_added = None, otherwise None.

Notes

If you don’t have access to proliferation/apoptosis gene sets, you can use the ones defined in cellrank for a specific organism. Alternatively, you can also use WOT without an estimate of initial growth rates. In that case, make sure to use several iterations in cellrank.external.kernels.WOTKernel.compute_transition_matrix() by increasing the growth_iters parameter. A value around 3 works well in most cases.

The markers used here were taken from the following sources: