lineage.HMM.M_step

Functions

sum_nonleaf_gammas(leaves_idx, gammas)

Sum of the gammas of the cells that are able to divide, that is,

get_all_zetas(tree, beta_array, MSD_array, gammas, T)

Sum of the list of all the zeta parent child for all the parent cells for a given state transition pair.

Module Contents

lineage.HMM.M_step.sum_nonleaf_gammas(leaves_idx, gammas)

Sum of the gammas of the cells that are able to divide, that is, sum the of the gammas of all the nonleaf cells. It is used in estimating the transition probability matrix. This is an inner component in calculating the overall transition probability matrix.

This is downward recursion.

Parameters:

  • leaves_idx -- leaf cell indices of the lineage tree

  • gammas (numpy.typing.NDArray[numpy.float64]) -- the gamma values for each lineage

Returns:

the sum of gamma values for each state for non-leaf cells.

Return type:

numpy.typing.NDArray[numpy.float64]

lineage.HMM.M_step.get_all_zetas(tree, beta_array, MSD_array, gammas, T)

Sum of the list of all the zeta parent child for all the parent cells for a given state transition pair. This is an inner component in calculating the overall transition probability matrix.

Parameters:

  • tree (scipy.sparse.csr_array) -- CSR array representing the lineage tree

  • beta_array (numpy.typing.NDArray[numpy.float64]) -- beta values. The conditional probability of states, given observations of the sub-tree rooted in cell_n

  • MSD_array (numpy.typing.NDArray[numpy.float64]) -- marginal state distribution

  • gammas (numpy.typing.NDArray[numpy.float64]) -- gamma values. The conditional probability of states, given the observation of the whole tree

  • T (numpy.typing.NDArray[numpy.float64]) -- transition probability matrix

Returns:

numerator for calculating the transition probabilities

Return type:

numpy.typing.NDArray[numpy.float64]