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Interactive lasso of regions of interest

This notebook shows the how to lasso the reigion of interest(ROI), which stored as an anndata object after lasso to facilitate subsequent analysis.

To operate in jupyter or jupyterlab, you need to install the following plug-in.

conda install nodejs
jupyter labextension install @ jupyter-widgets/jupyterlab-manager
jupyter labextension install plotlywidget
jupyter labextension install @ jupyterlab/plotly-extension

import spateo as st

Load data

We will be using a axolotl dataset from [Wei et al., 2022] (https://doi.org/10.1126/science.abp9444).

Here, we can get data directly from the functionst.sample.axolotl or link:

axolotl_2DPI: https://www.dropbox.com/s/7w2jxf41xazrqxo/axolotl_2DPI.h5ad?dl=1

adata = st.sample_data.axolotl(filename='axolotl_2DPI.h5ad')
adata

AnnData object with n_obs × n_vars = 7668 × 27324
    obs: 'CellID', 'spatial_leiden_e30_s8', 'Batch', 'cell_id', 'seurat_clusters', 'inj_uninj', 'D_V', 'inj_M_L', 'Annotation'
    var: 'Axolotl_ID', 'hs_gene'
    uns: 'Annotation_colors', '__type', 'color_key'
    obsm: 'X_spatial', 'spatial'
    layers: 'counts', 'log1p'
    obsp: 'connectivities', 'distances', 'spatial_connectivities', 'spatial_distances'

st.pl.space(adata,
            color=['Annotation'],
            pointsize=0.2,
            color_key=adata.uns['color_key'],
            show_legend='upper left',
            figsize=(5, 5))

Lasso data

a_lasso = st.tl.Lasso(adata)

a_lasso.vi_plot(group='Annotation', group_color='Annotation_colors')

sub_data = a_lasso.sub_adata
sub_data

View of AnnData object with n_obs × n_vars = 1643 × 27324
    obs: 'CellID', 'spatial_leiden_e30_s8', 'Batch', 'cell_id', 'seurat_clusters', 'inj_uninj', 'D_V', 'inj_M_L', 'Annotation'
    var: 'Axolotl_ID', 'hs_gene'
    uns: 'Annotation_colors', '__type', 'color_key'
    obsm: 'X_spatial', 'spatial'
    layers: 'counts', 'log1p'
    obsp: 'connectivities', 'distances', 'spatial_connectivities', 'spatial_distances'

st.pl.space(sub_data,
            color=['Annotation'],
            pointsize=0.2,
            color_key=adata.uns['color_key'],
            show_legend='upper left',
            figsize=(5, 5))