CellCloud Three-dimensional single-cell transcriptome imaging of thick tissues¶

Data obtained from https://elifesciences.org/reviewed-preprints/90029v1

In [1]:

import celldega as dega
import pandas as pd

import celldega as dega import pandas as pd

In [2]:

base_url = 'https://raw.githubusercontent.com/broadinstitute/scverse-owkin_thick_merfish/main/landscape_files'

base_url = 'https://raw.githubusercontent.com/broadinstitute/scverse-owkin_thick_merfish/main/landscape_files'

In [3]:

landscape = dega.viz.CellCloud(
    base_url=base_url,
    height=600,
    rotation_x=90,
)

landscape = dega.viz.CellCloud( base_url=base_url, height=600, rotation_x=90, )

In [4]:

df_sig = pd.read_parquet(base_url + '/df_sig.parquet')
mat = dega.clust.Matrix(df_sig)
mat.norm(axis='row', by='zscore')
mat.cluster()
cgm = dega.viz.Clustergram(matrix=mat, width=500, height=500)

df_sig = pd.read_parquet(base_url + '/df_sig.parquet') mat = dega.clust.Matrix(df_sig) mat.norm(axis='row', by='zscore') mat.cluster() cgm = dega.viz.Clustergram(matrix=mat, width=500, height=500)

In [5]:

dega.viz.spatial_clustergram(landscape, cgm)

dega.viz.spatial_clustergram(landscape, cgm)

Out[5]:

In [ ]: