Landscape-Heatmap Visium-HD¶

In [1]:

%load_ext autoreload
%autoreload 2
%env ANYWIDGET_HMR=1

%load_ext autoreload %autoreload 2 %env ANYWIDGET_HMR=1

env: ANYWIDGET_HMR=1

In [2]:

import pandas as pd
import celldega as dega

import pandas as pd import celldega as dega

In [3]:

base_url = 'https://raw.githubusercontent.com/broadinstitute/celldega_Visium_HD_mouse_brain/main/Visium_HD_mouse_brain'

base_url = 'https://raw.githubusercontent.com/broadinstitute/celldega_Visium_HD_mouse_brain/main/Visium_HD_mouse_brain'

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landscape_visium = dega.viz.Landscape(
    technology='Visium-HD',
    base_url=base_url,
    height=600,
    max_tiles_to_view = 10
)

landscape_visium = dega.viz.Landscape( technology='Visium-HD', base_url=base_url, height=600, max_tiles_to_view = 10 )

/var/folders/_6/bhs42vt57t1dkb59k4sy0p440000gp/T/ipykernel_42157/3604516923.py:1: UserWarning: Transformation matrix not found at https://raw.githubusercontent.com/broadinstitute/celldega_Visium_HD_mouse_brain/main/Visium_HD_mouse_brain/micron_to_image_transform.csv. Using identity.
  landscape_visium = dega.viz.Landscape(

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In [5]:

file_path = f'{base_url}/df_sig.parquet'
df_sig = pd.read_parquet(file_path)
top_genes = df_sig.sum(axis=1).sort_values(ascending=False).index.tolist()[:5000]
df_sig = df_sig.loc[top_genes]

file_path = f'{base_url}/df_sig.parquet' df_sig = pd.read_parquet(file_path) top_genes = df_sig.sum(axis=1).sort_values(ascending=False).index.tolist()[:5000] df_sig = df_sig.loc[top_genes]

In [6]:

mat = dega.clust.Matrix(data=df_sig)
mat.norm(axis='col', by='total')
mat.norm(axis='row', by='zscore')
mat.cluster()
cgm = dega.viz.Clustergram(matrix=mat, width=500, height=500)

mat = dega.clust.Matrix(data=df_sig) mat.norm(axis='col', by='total') mat.norm(axis='row', by='zscore') mat.cluster() cgm = dega.viz.Clustergram(matrix=mat, width=500, height=500)

In [7]:

dega.viz.landscape_clustergram(landscape_visium, cgm)

dega.viz.landscape_clustergram(landscape_visium, cgm)

Out[7]:

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