mofaflex.priors.GSFA#

class mofaflex.priors.GSFA(targets_obsm_key, s_b=20)#

Guided sparse factor analysis prior for CRISPR perturbation screens.

Important

This prior can only be used for factors.

Parameters:

targets_obsm_key (str) – The key in .obsm that contains the perturbation matrix.
s_b (float (default: 20)) – The $s_b$ parameter for the hyperprior on the non-zero probability.

Important

All methods and properties of this class are only accessible through the MofaFlex class.

Methods table#

`get_perturbation_effects`([ordered])	The perturbation effect matrix $\mat\beta$.
`get_posterior_inclusion_probabilities`([ordered])	The posterior inclusion probabilities $p$.

GSFA.get_perturbation_effects(ordered=False)#

The perturbation effect matrix $\mat\beta$.

Parameters:: ordered (bool (default: False)) – Whether to return the factors ordered by explained variance (highest to lowest).
Return type:: Mapping[str, DataFrame]

GSFA.get_posterior_inclusion_probabilities(ordered=False)#

The posterior inclusion probabilities $p$.

Parameters:: ordered (bool (default: False)) – Whether to return the factors ordered by explained variance (highest to lowest).
Return type:: Mapping[str, DataFrame]

`get_perturbation_effects`([ordered])	The perturbation effect matrix \(\mat\beta\).
`get_posterior_inclusion_probabilities`([ordered])	The posterior inclusion probabilities \(p\).