MIBI

[12]:

import os
import pandas as pd
import numpy as np
import scanpy as sc
import anndata as ad
import squidpy as sq
import matplotlib.pyplot as plt
import seaborn as sns

[2]:

import pysodb

[3]:

sc.set_figure_params(vector_friendly=False,format='pdf',transparent=True,dpi=50)
plt.rcParams["figure.figsize"] = (8, 8)

sns.set_style('white')

load a data using pysodb

[4]:

sodb = pysodb.SODB() # Initialization

/home/yzy/anaconda3/envs/SODB/lib/python3.9/site-packages/urllib3-1.26.12-py3.9.egg/urllib3/connectionpool.py:1045: InsecureRequestWarning: Unverified HTTPS request is being made to host 'gene.ai.tencent.com'. Adding certificate verification is strongly advised. See: https://urllib3.readthedocs.io/en/1.26.x/advanced-usage.html#ssl-warnings
  warnings.warn(

[5]:

# this data is from publication "A Structured Tumor-Immune Microenvironment in Triple Negative Breast Cancer Revealed by Multiplexed Ion Beam Imaging"

[6]:

# link in SODB: https://gene.ai.tencent.com/SpatialOmics/dataset?datasetID=47

[7]:

adata = sodb.load_experiment('keren2018a','p4')
# the first parameter is the name of the dataset
# the second parameter is the name of one experiment in the dataset

load experiment[p4] in dataset[keren2018a] from /home/yzy/anaconda3/envs/SODB/lib/python3.9/site-packages/pysodb-1.0.0-py3.9.egg/pysodb/cache/keren2018a/p4.h5ad

[8]:

adata

[8]:

AnnData object with n_obs × n_vars = 6643 × 36
    obs: 'SampleID', 'cellLabelInImage', 'cellSize', 'C', 'Na', 'Si', 'P', 'Ca', 'Fe', 'Background', 'B7H3', 'OX40', 'CD163', 'CSF-1R', 'Ta', 'Au', 'tumorYN', 'tumorCluster', 'Group', 'immuneCluster', 'immuneGroup', 'group_name', 'immuneGroup_name', 'all_group_name', 'leiden'
    uns: 'all_group_name_colors', 'group_name_colors', 'immuneGroup_name_colors', 'leiden', 'leiden_colors', 'moranI', 'neighbors', 'pca', 'spatial_neighbors', 'umap'
    obsm: 'X_pca', 'X_umap', 'spatial'
    varm: 'PCs'
    obsp: 'connectivities', 'distances', 'spatial_connectivities', 'spatial_distances'

play with Squidpy

display clusters

[9]:

sc.pl.embedding(adata,basis='spatial',color='all_group_name',s=30)

../_images/squidpy_pysodb_squidpy_MIBI_12_0.png

Neighborhood enrichment

[13]:

sq.gr.spatial_neighbors(adata)
sq.gr.nhood_enrichment(adata, cluster_key="all_group_name")
sq.pl.nhood_enrichment(adata, cluster_key="all_group_name")

/home/yzy/anaconda3/envs/SODB/lib/python3.9/site-packages/tqdm-4.64.1-py3.9.egg/tqdm/auto.py:22: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html
  from .autonotebook import tqdm as notebook_tqdm
100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:00<00:00, 1896.20/s]
/home/yzy/anaconda3/envs/SODB/lib/python3.9/site-packages/squidpy-1.1.2-py3.9.egg/squidpy/gr/_nhood.py:182: RuntimeWarning: invalid value encountered in divide
  zscore = (count - perms.mean(axis=0)) / perms.std(axis=0)
/home/yzy/anaconda3/envs/SODB/lib/python3.9/site-packages/squidpy-1.1.2-py3.9.egg/squidpy/pl/_graph.py:239: FutureWarning: X.dtype being converted to np.float32 from float64. In the next version of anndata (0.9) conversion will not be automatic. Pass dtype explicitly to avoid this warning. Pass `AnnData(X, dtype=X.dtype, ...)` to get the future behavour.
  ad = AnnData(X=array, obs={cluster_key: pd.Categorical(adata.obs[cluster_key].cat.categories)})

../_images/squidpy_pysodb_squidpy_MIBI_14_1.png

Interaction matrix and network centralities

[14]:

sq.gr.interaction_matrix(adata, cluster_key="all_group_name")
sq.pl.interaction_matrix(adata, cluster_key="all_group_name")

/home/yzy/anaconda3/envs/SODB/lib/python3.9/site-packages/squidpy-1.1.2-py3.9.egg/squidpy/pl/_graph.py:176: FutureWarning: X.dtype being converted to np.float32 from float64. In the next version of anndata (0.9) conversion will not be automatic. Pass dtype explicitly to avoid this warning. Pass `AnnData(X, dtype=X.dtype, ...)` to get the future behavour.
  ad = AnnData(X=array, obs={cluster_key: pd.Categorical(adata.obs[cluster_key].cat.categories)})

../_images/squidpy_pysodb_squidpy_MIBI_16_1.png

centrality score analysis

[15]:

sq.gr.centrality_scores(
    adata,
    cluster_key="all_group_name",
)
sq.pl.centrality_scores(adata, cluster_key="all_group_name", figsize=(20, 5), s=500)

../_images/squidpy_pysodb_squidpy_MIBI_18_0.png