Landscape View Xenium¶

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_Xenium_Prime_Human_Skin_FFPE_outs/main/Xenium_Prime_Human_Skin_FFPE_outs'
base_url = 'https://raw.githubusercontent.com/broadinstitute/celldega_Xenium_Prime_Ovarian_Cancer_FFPE_XRrun_outs_v2/main/Xenium_Prime_Ovarian_Cancer_FFPE_XRrun_outs'

# base_url = 'https://raw.githubusercontent.com/broadinstitute/celldega_Xenium_Prime_Human_Skin_FFPE_outs/main/Xenium_Prime_Human_Skin_FFPE_outs' base_url = 'https://raw.githubusercontent.com/broadinstitute/celldega_Xenium_Prime_Ovarian_Cancer_FFPE_XRrun_outs_v2/main/Xenium_Prime_Ovarian_Cancer_FFPE_XRrun_outs'

In [4]:

landscape = dega.viz.Landscape(
    technology='Xenium',
    base_url = base_url,
    height=500
)

landscape = dega.viz.Landscape( technology='Xenium', base_url = base_url, height=500 )

In [5]:

df_sig = pd.read_parquet('https://raw.githubusercontent.com/broadinstitute/celldega_Xenium_Prime_Ovarian_Cancer_FFPE_XRrun_outs_v2/main/Xenium_Prime_Ovarian_Cancer_FFPE_XRrun_outs/df_sig.parquet')                  
mat = dega.clust.Matrix(df_sig)
mat.norm(axis='col', by='total')
mat.norm(axis='row', by='zscore')
tmp = mat.cluster()
cgm = dega.viz.Clustergram(matrix=mat, width=500, height=500)

df_sig = pd.read_parquet('https://raw.githubusercontent.com/broadinstitute/celldega_Xenium_Prime_Ovarian_Cancer_FFPE_XRrun_outs_v2/main/Xenium_Prime_Ovarian_Cancer_FFPE_XRrun_outs/df_sig.parquet') mat = dega.clust.Matrix(df_sig) mat.norm(axis='col', by='total') mat.norm(axis='row', by='zscore') tmp = mat.cluster() cgm = dega.viz.Clustergram(matrix=mat, width=500, height=500)

In [6]:

dega.viz.landscape_clustergram(landscape, cgm)

dega.viz.landscape_clustergram(landscape, cgm)

Out[6]:

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