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"Tutorial 3: Automated Annotation of Cell Identities in mIHC Data\n",
"================================================================\n",
"\n",
"In this tutorial, we demonstrate how to use ImmunoPheno to annotate cell identities in a multiplexed IHC dataset using reference data stored in the ImmunoPhenoDB database. Specifically, we consider a human tonsil tissue section that has been profiled with PhenoCycler using a panel of 26 antibodies. For illustration purposes, we will only consider a small portion of the tissue section containing ~118k cells. The data can be found in this [link](https://www.dropbox.com/scl/fi/d03airv7b1bimyy8n99jz/codex_small.zip?rlkey=4php5lnz5a7r096kopb3h4b01&dl=0)."
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"import pandas as pd\n",
"import pickle\n",
"import numpy as np\n",
"import plotly.express as px\n",
"import seaborn as sns\n",
"from immunopheno.data_processing import ImmunoPhenoData\n",
"from immunopheno.connect import ImmunoPhenoDB_Connect\n",
"from immunopheno.plots import plot_filter_metrics\n",
"from sklearn.metrics.pairwise import euclidean_distances"
]
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"We can visualize the spatial location of the cells in the tissue:"
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