Note

This page was generated from 3D Reconstruction.ipynb. Interactive online version: . Some tutorial content may look better in light mode.

Three dims models reconstruction

This notebook demonstrates the process of 3D models reconstruction based on 3D spatial transcriptome data. This is done in the following five steps:

1. Construct the original 3D point cloud model (Embryo);

2. Construct the mesh model based on the 3D point cloud model (Embryo);

3. Construct the cell model based on the 3D point cloud model (Embryo);

4. Construct the voxel model based on the mesh model (Embryo);

5. Construct the subtype models based on the embryo model (CNS);

This example reconstructs 3D Drosophila Embryo/CNS models based on 3D spatial transcriptomics data of Drosophila Embryo.

import warnings
warnings.filterwarnings('ignore')
import numpy as np
import spateo as st

2023-07-25 09:35:00.085195: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT

Load the data

cpo = [(553, 1098, 277), (1.967, -6.90, -2.21), (0, 0, 1)]

adata = st.sample_data.drosophila(filename="E7-9h_cellbin.h5ad")
adata.uns["__type"] = "UMI"
adata

AnnData object with n_obs × n_vars = 25921 × 8136
    obs: 'area', 'slices', 'anno_cell_type', 'anno_tissue', 'anno_germ_layer', 'actual_stage'
    uns: '__type'
    obsm: '3d_align_spatial'
    layers: 'counts_X', 'spliced', 'unspliced'

3D reconstruction of Drosophila Embryo

Four types of 3D models can be reconstructed through spateo, including point cloud model, mesh model, cell model and voxel model. - The point cloud model and cell model are used to visualize gene expression matrix, cell annotation results and other information. - The mesh model is used to calculate the morphological characteristics of the 3D model, including the length, width, height, volume, surface area, etc. of the model. - The voxel model is used for gene expression matrix interpolation and smoothing.

In addition to realizing 3D reconstruction through the following code, you can also choose to use spateo-viewer to reconstruct 3D models.

3D reconstruction of original point cloud model

embryo_pc, plot_cmap = st.tdr.construct_pc(adata=adata.copy(), spatial_key="3d_align_spatial", groupby="anno_tissue", key_added="tissue", colormap="rainbow")
st.pl.three_d_plot(model=embryo_pc, key="tissue", model_style="points", colormap=plot_cmap, jupyter="static", cpo=cpo)
st.tdr.save_model(model=embryo_pc, filename="embryo_pc_model.vtk")

3D reconstruction of mesh model

embryo_mesh, _, _ = st.tdr.construct_surface(pc=embryo_pc, key_added="tissue", alpha=0.6, cs_method="marching_cube", cs_args={"mc_scale_factor": 0.8}, smooth=5000, scale_factor=1.08)
st.pl.three_d_plot(model=st.tdr.collect_models([embryo_mesh, embryo_pc]), key="tissue", model_style=["surface", "points"], jupyter="static", cpo=cpo)
st.tdr.save_model(model=embryo_mesh, filename="embryo_mesh_model.vtk")

3D reconstruction of cell mesh model

# Add cell radius info
obs_index = embryo_pc.point_data["obs_index"].tolist()
area = adata[obs_index, :].obs["area"].values
cell_radius = pow(np.asarray(area), 1 / 2)
st.tdr.add_model_labels(model=embryo_pc, labels=cell_radius, key_added="cell_radius", where="point_data", colormap="hot_r", inplace=True)
embryo_cells = st.tdr.construct_cells(pc=embryo_pc, cell_size=embryo_pc.point_data["cell_radius"], geometry="sphere", factor=0.2)
st.pl.three_d_plot(model=embryo_cells, key="tissue", jupyter="static", cpo=cpo)
st.tdr.save_model(model=embryo_cells, filename="embryo_cells_mesh_model.vtk")

3D reconstruction of voxel model

embryo_voxel, _ = st.tdr.voxelize_mesh(mesh=embryo_mesh, voxel_pc=None, key_added="tissue", label="embryo_voxel", color="gainsboro", smooth=500)
st.pl.three_d_plot(model=embryo_voxel, key="tissue", jupyter="static", cpo=cpo)
st.tdr.save_model(model=embryo_voxel, filename="embryo_voxel_model.vtk")

3D reconstruction of subtype models (Drosophila CNS)

subtype = "CNS"
subtype_rpc = st.tdr.three_d_pick(model=embryo_pc, key="tissue", picked_groups=subtype)[0]
subtype_tpc = st.tdr.interactive_rectangle_clip(model=subtype_rpc, key="tissue", invert=True)[0]

subtype_mesh, subtype_pc, _ = st.tdr.construct_surface(
    pc=subtype_tpc, key_added="tissue", label=subtype, color="purple", alpha=0.6, cs_method="marching_cube", cs_args={"mc_scale_factor": 0.8}, smooth=5000, scale_factor=1
)

st.pl.three_d_multi_plot(
    model=st.tdr.collect_models(
        [
            st.tdr.collect_models([embryo_mesh, subtype_pc]),
            st.tdr.collect_models([embryo_mesh, subtype_mesh]),
            st.tdr.collect_models([embryo_mesh, subtype_mesh, subtype_pc])
        ]
    ),
    key="tissue",
    model_style=[["surface", "points"], "surface", ["surface", "surface", "points"]],
    model_size=3,
    shape=(1, 3),
    jupyter="static",
    cpo=[cpo]
)