Marker analysis

• fold change heatmaps

import braian
import braian.config
import braian.plot as bap
import braian.stats as bas

import plotly.io as pio
from pathlib import Path

# This ensures BraiAn's figures works in multiple places:
pio.renderers.default = "plotly_mimetype+notebook"

root_dir = Path.cwd().absolute().parent      # braian experiment root
config_file = root_dir/"config_example.yml"  # configuration path
config = braian.config.BraiAnConfig(config_file, root_dir/"data") # we instantiate the config

import braian import braian.config import braian.plot as bap import braian.stats as bas import plotly.io as pio from pathlib import Path # This ensures BraiAn's figures works in multiple places: pio.renderers.default = "plotly_mimetype+notebook" root_dir = Path.cwd().absolute().parent # braian experiment root config_file = root_dir/"config_example.yml" # configuration path config = braian.config.BraiAnConfig(config_file, root_dir/"data") # we instantiate the config

ontology = config.read_atlas_ontology()

ontology = config.read_atlas_ontology()

experiment = config.experiment_from_csv(fill_nan=False)

experiment = config.experiment_from_csv(fill_nan=False)

group_hc_similarity = braian.AnimalGroup(
    experiment.hc.name,
    [bas.markers_similarity_index(b.merge_hemispheres(), "cFos", "Arc") for b in experiment.hc.animals],
    hemisphere_distinction=False,
    brain_ontology=ontology,
    fill_nan=True
)

group_ctx_similarity = braian.AnimalGroup(
    experiment.ctx.name,
    [bas.markers_similarity_index(b.merge_hemispheres(), "cFos", "Arc") for b in experiment.ctx.animals],
    hemisphere_distinction=False,
    brain_ontology=ontology,
    fill_nan=True
)

group_fc_similarity = braian.AnimalGroup(
    experiment.fc.name,
    [bas.markers_similarity_index(b.merge_hemispheres(), "cFos", "Arc") for b in experiment.fc.animals],
    hemisphere_distinction=False,
    brain_ontology=ontology,
    fill_nan=True
)

group_hc_similarity = braian.AnimalGroup( experiment.hc.name, [bas.markers_similarity_index(b.merge_hemispheres(), "cFos", "Arc") for b in experiment.hc.animals], hemisphere_distinction=False, brain_ontology=ontology, fill_nan=True ) group_ctx_similarity = braian.AnimalGroup( experiment.ctx.name, [bas.markers_similarity_index(b.merge_hemispheres(), "cFos", "Arc") for b in experiment.ctx.animals], hemisphere_distinction=False, brain_ontology=ontology, fill_nan=True ) group_fc_similarity = braian.AnimalGroup( experiment.fc.name, [bas.markers_similarity_index(b.merge_hemispheres(), "cFos", "Arc") for b in experiment.fc.animals], hemisphere_distinction=False, brain_ontology=ontology, fill_nan=True )

from IPython.display import display

depths = 7000 # in µm

bap.heatmap(
    bd1=group_hc_similarity.mean["cFos+Arc"],
    bd2=group_fc_similarity.mean["cFos+Arc"],
    brain_regions=ontology.get_regions("summary structures"),
    orientation="frontal", depth=depths,
    show_acronyms=False,
)

from IPython.display import display depths = 7000 # in µm bap.heatmap( bd1=group_hc_similarity.mean["cFos+Arc"], bd2=group_fc_similarity.mean["cFos+Arc"], brain_regions=ontology.get_regions("summary structures"), orientation="frontal", depth=depths, show_acronyms=False, )

foldchange_hc_fc = braian.AnimalGroup(
    group_fc_similarity.name,
    [bas.fold_change(b, group_hc_similarity) for b in group_fc_similarity.animals],
    hemisphere_distinction=False,
    brain_ontology=ontology,
    fill_nan=True
)

foldchange_hc_fc = braian.AnimalGroup( group_fc_similarity.name, [bas.fold_change(b, group_hc_similarity) for b in group_fc_similarity.animals], hemisphere_distinction=False, brain_ontology=ontology, fill_nan=True )

from IPython.display import display

depths = (3500, 5000, 7000, 8000, 9000) # in µm

for depth, heatmap in bap.heatmap(
    foldchange_hc_fc.mean["cFos+Arc"],
    brain_regions=ontology.get_regions("summary structures"),
    orientation="frontal", depth=depths,
    centered_cmap=True, cmin=0, ccenter=1, cmax=5
).items():
    display(heatmap)

from IPython.display import display depths = (3500, 5000, 7000, 8000, 9000) # in µm for depth, heatmap in bap.heatmap( foldchange_hc_fc.mean["cFos+Arc"], brain_regions=ontology.get_regions("summary structures"), orientation="frontal", depth=depths, centered_cmap=True, cmin=0, ccenter=1, cmax=5 ).items(): display(heatmap)

3500.00  5000.00  7000.00  8000.00  9000.00