{
"cells": [
{
"cell_type": "markdown",
"id": "8ef9e021-1b2e-4086-868a-86d7e77b6f04",
"metadata": {},
"source": [
"# MERFISH mouse liver\n",
"\n",
"In this notebook, we will use ovrlpy to investigate the [Vizgen MERFISH's mouse liver dataset](https://info.vizgen.com/mouse-liver-data).\n",
"\n",
"We want to create a signal embedding of the transcriptome, and a vertical signal incoherence map to identify locations with a high risk of containing spatial doublets."
]
},
{
"attachments": {},
"cell_type": "markdown",
"id": "c88b9df5",
"metadata": {},
"source": [
"## Settings and Imports\n",
"\n",
"First, let's define settings and input files."
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "7f26e482-97a7-4c1b-99f6-13f86119e183",
"metadata": {},
"outputs": [],
"source": [
"from pathlib import Path\n",
"\n",
"import matplotlib.pyplot as plt\n",
"\n",
"import ovrlpy"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "59c7c39e-3c57-413c-b295-dad2b315b3fa",
"metadata": {},
"outputs": [],
"source": [
"sample_nr = 1\n",
"slice_nr = 1\n",
"\n",
"data_path = Path(\"/dh-projects/ag-ishaque/raw_data/vizgen-merfish/vz-liver-showcase\")\n",
"\n",
"coordinate_file = (\n",
" data_path / f\"Liver{sample_nr}Slice{slice_nr}\" / \"detected_transcripts.csv\"\n",
")"
]
},
{
"cell_type": "markdown",
"id": "e7d943a4-4ff9-4b03-83f9-a78b860a18d7",
"metadata": {},
"source": [
"## Loading the data\n",
"\n",
"Next, we want to load the data."
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "dd6576df-592f-4c2a-8e18-9706d4a4462b",
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Number of transcripts: 417,243,171\n"
]
}
],
"source": [
"coordinate_df = ovrlpy.io.read_MERFISH(coordinate_file)\n",
"\n",
"print(f\"Number of transcripts: {len(coordinate_df):,}\")"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "a02c7877-0633-4971-bef6-d9ae338bd65c",
"metadata": {},
"outputs": [
{
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