![](\"https://raw.githubusercontent.com/Xiaojieqiu/jungle/master/differential_geometry.png\")
\n",
"\n",
"In this tutorial, we will cover following topics:\n",
"\n",
"- learn contionus RNA velocity vector field functions in different spaces (e.g. umap or pca space)\n",
"- calculate RNA acceleration, curvature matrices (**cell by gene**)\n",
"- rank genes based on RNA velocity, curvature and acceleration matrices \n",
"- calculate RNA Jacobian tensor (**cell by gene by gene**) for genes with high PCA loadings.\n",
"- rank genes based on the jacobian tensor, which including:\n",
" - rank genes with strong postive or negative self-interaction (`divergence` ranking)\n",
" - other rankings, ranking modes including `full_reg`, `full_eff`, `eff`, `reg` and `int`\n",
"- build and visualize gene regulatory network with top ranked genes \n",
"- gene enrichment analyses of top ranked genes\n",
"- visualize Jacobian derived regulatory interactions across cells \n",
"- visualize gene expression, velocity, acceleration and curvature kinetics along pseudotime trajectory\n",
"- learn and visualize models of cell-fate transitions"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Import relevant packages"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/xiaojieqiu/opt/anaconda3/envs/dynamo_mkl/lib/python3.9/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
" from .autonotebook import tqdm as notebook_tqdm\n"
]
}
],
"source": [
"# !pip install dynamo-release --upgrade --quiet\n",
"\n",
"import dynamo as dyn\n",
"\n",
"# set white background\n",
"dyn.configuration.set_figure_params(background='white') \n",
"\n",
"import matplotlib.pyplot as plt \n",
"import numpy as np \n",
"import pandas as pd\n",
"from gseapy.plot import barplot, dotplot\n",
"\n",
"import warnings\n",
"warnings.filterwarnings('ignore')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Set the logging level. Various logging level can be setted according to your needs:\n",
"\n",
"- DEBUG: useful for dynamo development, show all logging information, including those debugging information\n",
"- INFO: useful for most dynamo users, show detailed dynamo running information\n",
"- WARNING: show only warning information\n",
"- ERROR: show only exception or error information\n",
"- CRITICAL: show only critical information"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"%matplotlib inline\n",
"from dynamo.dynamo_logger import main_info, LoggerManager\n",
"LoggerManager.main_logger.setLevel(LoggerManager.INFO)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Load processed data or data preprocessing \n",
"\n",
"If you followed the **zebrafish pigmentation** tutorial, you can load the processed zebrafish adata object here for all downstream analysis. "
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"|-----> Downloading data to ./data/zebrafish.h5ad\n"
]
},
{
"data": {
"text/plain": [
"AnnData object with n_obs × n_vars = 4181 × 16940\n",
" obs: 'split_id', 'sample', 'Size_Factor', 'condition', 'Cluster', 'Cell_type', 'umap_1', 'umap_2', 'batch'\n",
" layers: 'spliced', 'unspliced'"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"adata = dyn.sample_data.zebrafish()\n",
"adata"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"|-----> Downloading data to ./data/zebrafish.h5ad\n",
"|-----> Running monocle preprocessing pipeline...\n",
"|-----------> filtered out 14 outlier cells\n",
"|-----------> filtered out 12746 outlier genes\n",
"|-----> PCA dimension reduction\n",
"|-----> | \n", " | tmsb4x | \n", "tmsb4x_values | \n", "rplp2l | \n", "rplp2l_values | \n", "rpl7a | \n", "rpl7a_values | \n", "pvalb1 | \n", "pvalb1_values | \n", "gfap | \n", "gfap_values | \n", "... | \n", "slc4a4a | \n", "slc4a4a_values | \n", "ccna2 | \n", "ccna2_values | \n", "ddc | \n", "ddc_values | \n", "top2a | \n", "top2a_values | \n", "slc6a2 | \n", "slc6a2_values | \n", "
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | \n", "si:dkey-183i3.5 | \n", "0.001557 | \n", "si:dkey-183i3.5 | \n", "0.001826 | \n", "si:dkey-183i3.5 | \n", "0.001525 | \n", "si:dkey-183i3.5 | \n", "0.001295 | \n", "mt2 | \n", "0.001241 | \n", "... | \n", "mt2 | \n", "0.000326 | \n", "hmgn2 | \n", "0.001233 | \n", "tubb5 | \n", "0.000438 | \n", "hmgn2 | \n", "0.000979 | \n", "tubb5 | \n", "0.000425 | \n", "
| 1 | \n", "zgc:136930 | \n", "0.001212 | \n", "calm2b | \n", "0.001520 | \n", "calm2b | \n", "0.001270 | \n", "mcl1b | \n", "0.001133 | \n", "gfap | \n", "0.001165 | \n", "... | \n", "gfap | \n", "0.000276 | \n", "hmgb2a | \n", "0.000899 | \n", "elavl4 | \n", "0.000422 | \n", "hmgb2a | \n", "0.000703 | \n", "elavl4 | \n", "0.000409 | \n", "
2 rows × 934 columns
\n", "