Plot GRN

[1]:

from grnet.clusters import CellClasses
from grnet.models import PC
from grnet.plot import grnplot
from grnet.toydata import load_dataset, load_metadata
import matplotlib.pyplot as plt

data loading

[2]:

data = load_dataset("prototype1")
meta = load_metadata("prototype1")

lst_data = [
    data.loc[meta.cluster == v, :].iloc[:, :5] for v in meta.cluster.unique()
]

GRN formation with PC algorithm

[3]:

models = [PC(v) for v in lst_data]

for v in models:
    v.estimate()

INFO:pgmpy: Datatype (N=numerical, C=Categorical Unordered, O=Categorical Ordered) inferred from data:
 {'gene_1': 'N', 'gene_2': 'N', 'gene_3': 'N', 'gene_4': 'N', 'gene_5': 'N'}
INFO:pgmpy: Datatype (N=numerical, C=Categorical Unordered, O=Categorical Ordered) inferred from data:
 {'gene_1': 'N', 'gene_2': 'N', 'gene_3': 'N', 'gene_4': 'N', 'gene_5': 'N'}
INFO:pgmpy: Datatype (N=numerical, C=Categorical Unordered, O=Categorical Ordered) inferred from data:
 {'gene_1': 'N', 'gene_2': 'N', 'gene_3': 'N', 'gene_4': 'N', 'gene_5': 'N'}
INFO:pgmpy: Datatype (N=numerical, C=Categorical Unordered, O=Categorical Ordered) inferred from data:
 {'gene_1': 'N', 'gene_2': 'N', 'gene_3': 'N', 'gene_4': 'N', 'gene_5': 'N'}
INFO:pgmpy: Datatype (N=numerical, C=Categorical Unordered, O=Categorical Ordered) inferred from data:
 {'gene_1': 'N', 'gene_2': 'N', 'gene_3': 'N', 'gene_4': 'N', 'gene_5': 'N'}

Plotting GRN

[4]:

fig, ax = plt.subplots(figsize=(4, 4))

grnplot(models[0], ax=ax)

ax.set(title="cluster_1 (prototype1)");

Customize plot aesthetics

color

[5]:

fig, ax = plt.subplots(figsize=(4, 4))

grnplot(models[0], ax=ax, color="C1")

ax.set(title="cluster_1 (prototype1)");

edgecolor

[6]:

fig, ax = plt.subplots(figsize=(4, 4))

grnplot(models[0], ax=ax, edgecolor="C1")

ax.set(title="cluster_1 (prototype1)");

kwargs regarding annotations

[7]:

fig, ax = plt.subplots(1, 4, figsize=(16, 4))

arguments = [
    {"fontsize": "large"}, # default :"x-small"
    {"annot_radius": 0.5}, # default: 1.1
    {"annot_xloc": 2}, # default: -1
    {"annot_yloc": 2} # default: -0.4
]

for i, v in enumerate(arguments):
    grnplot(models[0], ax=ax[i], **v)
    ax[i].set(title=list(v.keys())[0])