API

Inference

`infer_with_twinfer`	Score gene pairs with the covariance decomposition (and the cross-time correlation when there are several time points).
`classify_inference_scenario`	Inference scenario (1-4) of each pair from its three z-scores (arrays or scalars); NaN in a needed z-score gives <NA>.
`q_values_of_z_rho`	BH q-values of z_rho: two-sided normal p-values `2 * P(Z > \|z_rho\|)`, corrected over all pairs given (NaN excluded).
`q_values_of_z_rho_Delta`	BH q-values of z_rho_Delta (two-sided normal p-values), corrected over the pairs whose z_rho passes BH (q_rho <= fdr); NaN for the other pairs (as Stage III of the TwinScore procedure: BH over the Stage I pairs).
`twin_stats`	Statistics of two genes in N twin pairs.
`clone_twin_stats`	Statistics of one gene pair: x, y one value per cell, clone one label per cell.
`clone_twin_stats_matrix`	Statistics of every pair (column of X, column of Y) for cells with clone labels.
`sister_arrays`	Arrange a long table into per-gene sister arrays.

Ranked lists of gene pairs, one per score.

`network_from_scenarios`	Turn the output of infer_with_twinfer into the inputs of plot_grn.
`plot_grn`	Plot a signed, weighted directed GRN.

`process_param_set`	Processes a set of parameters for a Gillespie simulation, running the simulation for a specified number of cells and handling the results.
`run_simulation`	Simulates the dynamics of a population of cells using the Gillespie algorithm.