scphylo.tl.scite#

scphylo.tl.scite(df_input, alpha, beta, n_iters=90000, n_restarts=3, experiment=False)[source]#

Solving using SCITE.

Tree inference for single-cell data [SCITE].

Parameters:

df_input¶ (pandas.DataFrame) – Input genotype matrix in which rows are cells and columns are mutations. Values inside this matrix show the presence (1), absence (0) and missing entires (3).
alpha¶ (float) – False positive error rate.
beta¶ (float) – False negative error rate.
n_iters¶ (int, optional) – Number of iterations, by default 90000
n_restarts¶ (int, optional) – Number of restarts, by default 3
experiment¶ (bool, optional) – Is in the experiment mode (the log won’t be shown), by default False

Returns:

A conflict-free matrix in which rows are cells and columns are mutations. Values inside this matrix show the presence (1) and absence (0).

Return type:

pandas.DataFrame

Examples#