Reconstruct tree by Trisicell-PartF

This example shows how to assess a phylogenetic tree using Trisicell-PartF on a binary single-cell genotype matrix.

import scphylo as scp

# sphinx_gallery_thumbnail_path = "_static/thumbnails/trisicell-partf.png"

First, we load a binary test single-cell genotype data.

df_in = scp.datasets.test()
df_in.head()

	mut0	mut1	mut2	mut3	mut4	mut5	mut6	mut7	mut8	mut9	mut10	mut11	mut12	mut13	mut14	mut15	mut16	mut17	mut18	mut19
cellIDxmutID
cell0	1	1	1	1	1	1	1	0	3	3	0	3	0	0	0	3	0	0	0	0
cell1	3	0	0	0	0	0	3	0	1	1	3	1	0	0	3	0	0	1	1	1
cell2	0	0	0	0	0	0	0	1	1	3	1	1	0	0	3	1	1	1	1	0
cell3	0	0	0	0	0	0	0	3	1	0	0	1	0	0	0	1	1	1	0	0
cell4	0	0	0	0	0	0	0	1	1	1	1	1	0	0	3	0	0	0	0	0

Then, using scphylo.tl.partition_function() we calculate the probability of cell6 and cell17 seeded by mut12

probs = scp.tl.partition_function(
    df_in,
    alpha=0.000001,
    beta=0.1,
    n_samples=100,
    n_batches=10,
    muts=["mut12"],
    cells=["cell6", "cell17"],
)
probs.mean(axis=1).round(4).values[0]

elapsed time: 0:00:02.430325

np.float64(0.8924)

Estimated memory usage: 439 MB