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#

Reconstruct tree by SCITE

Reconstruct tree by SCITE