{
"cells": [
{
"cell_type": "markdown",
"id": "46d6203c",
"metadata": {},
"source": [
"# Intestinal organoid differentiation - Fate mapping\n",
"\n",
"Fate analysis using velocities derived from metabolic labeling."
]
},
{
"cell_type": "markdown",
"id": "8e723a08-3492-438d-9fd2-560876e9bbd8",
"metadata": {},
"source": [
"## Library imports"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "d2be5ed5-77fc-4109-b299-7e379c41811c",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Global seed set to 0\n"
]
}
],
"source": [
"import sys\n",
"\n",
"import numpy as np\n",
"import pandas as pd\n",
"from scipy.sparse import csr_matrix\n",
"\n",
"import matplotlib.pyplot as plt\n",
"import mplscience\n",
"import seaborn as sns\n",
"\n",
"import cellrank as cr\n",
"import scanpy as sc\n",
"import scvelo as scv\n",
"from anndata import AnnData\n",
"\n",
"from cr2 import get_state_purity, get_var_ranks, plot_state_purity, running_in_notebook\n",
"\n",
"sys.path.extend([\"../../\", \".\"])\n",
"from paths import DATA_DIR, FIG_DIR # isort: skip # noqa: E402"
]
},
{
"cell_type": "markdown",
"id": "de031818-29bd-409f-ade3-5701d762f9c0",
"metadata": {},
"source": [
"## General settings"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "8238e664-ac3e-4637-b337-39439062040f",
"metadata": {},
"outputs": [],
"source": [
"sc.settings.verbosity = 3\n",
"scv.settings.verbosity = 3\n",
"cr.settings.verbosity = 2"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "58a3e22b-54d9-4319-a119-0514bc25ccfb",
"metadata": {},
"outputs": [],
"source": [
"scv.settings.set_figure_params(\"scvelo\")"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "f1d1620d",
"metadata": {},
"outputs": [],
"source": [
"SAVE_FIGURES = False\n",
"\n",
"if SAVE_FIGURES:\n",
" (FIG_DIR / \"labeling_kernel\").mkdir(parents=True, exist_ok=True)\n",
"\n",
"FIGURE_FORMAT = \"pdf\""
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "09b62837",
"metadata": {},
"outputs": [],
"source": [
"(DATA_DIR / \"sceu_organoid\" / \"results\").mkdir(parents=True, exist_ok=True)"
]
},
{
"cell_type": "markdown",
"id": "937c9cbb",
"metadata": {},
"source": [
"## Data loading"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "5c201510-d600-4c16-be5c-2da40e50b6c7",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"AnnData object with n_obs × n_vars = 3452 × 2000\n",
" obs: 'experiment', 'labeling_time', 'cell_type', 'som_cluster_id', 'cell_type_merged', 'initial_size', 'n_counts'\n",
" var: 'ensum_id', 'gene_count_corr', 'means', 'dispersions', 'dispersions_norm', 'highly_variable'\n",
" uns: 'cell_type_colors', 'neighbors', 'pca', 'umap'\n",
" obsm: 'X_pca', 'X_umap', 'X_umap_paper'\n",
" varm: 'PCs'\n",
" layers: 'labeled', 'total', 'unlabeled'\n",
" obsp: 'connectivities', 'distances'"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"adata = sc.read(DATA_DIR / \"sceu_organoid\" / \"processed\" / \"preprocessed.h5ad\")\n",
"adata"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "3d73bf3a-5906-460b-8f11-ad9932ae8618",
"metadata": {},
"outputs": [
{
"data": {
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