{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Basic use 1: Mouse to human" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Here is a brief demonstration on how to use TransBrain to map the phenptype from mouse to human. The example data used in this tutorial can be download from ``exampledata`` directory of our [GitHub repository](https://github.com/ibpshangzheng/transbrain/tree/main/transbrain/exampledata)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Step 1: Prepare input data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "There are two ways to input data. One is that you already have region-level phenotype data as a ``CSV`` table which follows the format and region order in the [provided template file](https://github.com/ibpshangzheng/transbrain/tree/main/transbrain/exampledata). The DataFrame contains two columns: ``['Anatomical Name', 'Phenotype']``.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Here we load the example mouse data table." ] }, { "cell_type": "code", "execution_count": 52, "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "\n", "# Example mouse data\n", "mouse_phenotype = pd.read_csv('../../../transbrain/exampledata/mouse/mouse_all_example_data.csv',index_col=0)" ] }, { "cell_type": "code", "execution_count": 53, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
| \n", " | Phenotype | \n", "
|---|---|
| Anatomical Name | \n", "\n", " |
| ACAd | \n", "0.604528 | \n", "
| ACAv | \n", "0.369476 | \n", "
| PL | \n", "1.139296 | \n", "
| ILA | \n", "0.539155 | \n", "
| ORBl | \n", "0.000000 | \n", "
| ... | \n", "... | \n", "
| MTN | \n", "4.848956 | \n", "
| ILM | \n", "5.223949 | \n", "
| GENv | \n", "0.211631 | \n", "
| EPI | \n", "3.944129 | \n", "
| RT | \n", "1.150901 | \n", "
68 rows × 1 columns
\n", "| \n", " | Anatomical Name | \n", "Atlas Index | \n", "
|---|---|---|
| 0 | \n", "ACAd | \n", "1 | \n", "
| 1 | \n", "ACAv | \n", "2 | \n", "
| 2 | \n", "AId | \n", "3 | \n", "
| 3 | \n", "AIp | \n", "4 | \n", "
| 4 | \n", "AIv | \n", "5 | \n", "
| ... | \n", "... | \n", "... | \n", "
| 63 | \n", "MTN | \n", "64 | \n", "
| 64 | \n", "ILM | \n", "65 | \n", "
| 65 | \n", "GENv | \n", "66 | \n", "
| 66 | \n", "EPI | \n", "67 | \n", "
| 67 | \n", "RT | \n", "68 | \n", "
68 rows × 2 columns
\n", "| \n", " | Phenotype | \n", "
|---|---|
| Anatomical Name | \n", "\n", " |
| ACAd | \n", "0.604520 | \n", "
| ACAv | \n", "0.369486 | \n", "
| PL | \n", "1.139259 | \n", "
| ILA | \n", "0.539203 | \n", "
| ORBl | \n", "0.000038 | \n", "
| ... | \n", "... | \n", "
| MTN | \n", "4.848961 | \n", "
| ILM | \n", "5.223915 | \n", "
| GENv | \n", "0.211644 | \n", "
| EPI | \n", "3.944127 | \n", "
| RT | \n", "1.150919 | \n", "
68 rows × 1 columns
\n", "| \n", " | Phenotype | \n", "
|---|---|
| A8m | \n", "-0.036852 | \n", "
| A8dl | \n", "-0.037943 | \n", "
| A9l | \n", "-0.048855 | \n", "
| A6dl | \n", "-0.023955 | \n", "
| A6m | \n", "-0.005824 | \n", "
| ... | \n", "... | \n", "
| Otha | \n", "0.286260 | \n", "
| mPFtha | \n", "0.568262 | \n", "
| lPFtha | \n", "0.224644 | \n", "
| rTtha | \n", "0.732510 | \n", "
| PPtha | \n", "0.469096 | \n", "
127 rows × 1 columns
\n", "