Contents

Basic Analysis in SptialTis

SpatialTis provides some basic analysis

  • Cell Components

  • Cell Density

  • Cell Morphology

  • Cell Co-occurrence

To run the following analysis, you need to Download the data.

[1]:

import warnings
warnings.filterwarnings("ignore", category=FutureWarning)

[2]:

import anndata as ad

data = ad.read_h5ad("../data/imc_data.h5ad")
data

[2]:

AnnData object with n_obs × n_vars = 1776974 × 38
    obs: 'area', 'eccentricity', 'islet_id', 'centroid', 'image', 'case', 'slide', 'part', 'group', 'stage', 'cell_cat', 'cell_type'
    var: 'markers'

[3]:

import spatialtis as st
import spatialtis.plotting as sp
from spatialtis import CONFIG

CONFIG.EXP_OBS = ["stage", "case", "part", "image"]
CONFIG.CELL_TYPE_KEY = "cell_type"
CONFIG.MARKER_KEY = "markers"
CONFIG.CENTROID_KEY = "centroid"

Cell Components

Used to calculate the fractions of cells.

[4]:

st.cell_components(data)

⏳ Cell Components

📦 Added to AnnData, uns: 'cell_components'

⏱ 488ms

[4]:

We can visualize it, the default is static rendering.

[5]:

islets_cells = ['gamma', 'delta', 'alpha', 'beta',]
colors = ["#7aafde","#1b65b0","#fc7f71","#db060b"][::-1]
sp.cell_components(data,
                   ["stage", "case"],
                   selected_types=islets_cells,
                   group_order={'stage':['Non-diabetic', 'Onset', 'Long-duration'],
                               'case':[6126,6134,6386,6278,6362,6414,6228,6380,6418,6180,6089,6264]},
                   palette=colors,
                   size=(5, 3.5),
                   title="Cell components of Islet cells",
                   yaxis_title="% of cell type")
../_images/tutorial_2-basic_analysis_7_0.png 
[5]:

Alternatively, you can pass use="interactive" to used bokeh, put your mouse on it to see extra information.

[6]:

sp.cell_components(data,
                   ["stage", "case"],
                   use="interactive",
                   selected_types=islets_cells[::-1],
                   group_order={'stage':['Non-diabetic', 'Onset', 'Long-duration'],
                               'case':[6126,6134,6386,6278,6362,6414,6228,6380,6418,6180,6089,6264]},
                   palette=colors,
                   title="Cell components of Islet cells",
                   yaxis_title="% of cell type")

[6]:

Cell Density

Used to calculate the density of cells

[7]:

st.cell_density(data, ratio=0.001)

⏳ Cell Density

📦 Added to AnnData, uns: 'cell_density'

⏱ 20s29ms

[7]:



[8]:

sp.cell_density(data, ['stage'], selected_types=['alpha', 'beta', 'gamma', 'delta'],
                group_order={'stage':['Non-diabetic', 'Onset', 'Long-duration'],},
                             size=(4, 3))
../_images/tutorial_2-basic_analysis_12_0.png 
[8]:

Cell Co-occurrence

To determine whether two cells will occur in the same ROI

[9]:

st.cell_co_occurrence(data)

⏳ Cell Co-occurrence

📦 Added to AnnData, uns: 'co_occurrence'

⏱ 853ms

[9]:



[10]:

sp.cell_co_occurrence(data, xtickslabel_rotation=90)
../_images/tutorial_2-basic_analysis_15_0.png 
[10]:



[11]:

sp.cell_co_occurrence(data, ['stage'], use="heatmap")
../_images/tutorial_2-basic_analysis_16_0.png 
[11]:

Cell Morphology

The distribution of one of your cell’s morphology metrics, if your morphology information is available.

Here we can get the cell’s eccentricity.

[12]:

st.cell_morphology(data, metric_key="eccentricity")

⏳ Cell Morphology

📦 Added to AnnData, uns: 'morphology'

⏱ 4s360ms

[12]:



[13]:

sp.cell_morphology(data, ['stage', 'part'], selected_types=islets_cells, size=(8, 3))
../_images/tutorial_2-basic_analysis_19_0.png 
[13]:



[14]:
Introduction to SpatialTis Spatial Analysis