{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "58c9aafb",
   "metadata": {},
   "source": [
    "# Inference and Analysis of Gene Expression Rhythmicity using GeneRhythm\n",
    "This tutorial provides a step-by-step guide on performing inference, analysis, and visualization of gene expression rhythmicity in a single dataset using GeneRhythm. We demonstrate the diverse capabilities of GeneRhythm by applying it to scRNA-seq data obtained from mouse tissue samples.\n",
    "\n",
    "GeneRhythm leverages user-provided gene expression data by integrating wavelet transformation with deep generative modeling. This approach enables the extraction of frequency-domain features that complement traditional time-domain analyses, allowing for a more comprehensive understanding of gene expression dynamics. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d5d4797e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import subprocess\n",
    "from Build_graph import *\n",
    "from Frequency_extract import *\n",
    "from GCN_VAE import *\n",
    "from Show_result import *"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "07a449c4",
   "metadata": {},
   "source": [
    "# Part 1: Data loading, time and frequency information acquisition\n",
    "## Obtain time information with monocle3\n",
    "GeneRhythm firstly utilized monocle3 to obtain the trajectory information of single-cell RNA-seq data. trajectory_inference.R is the script to run monocle3. dataset indicated the name of dataset. mtx, barcode and gene indicate the position of the single-cell RNA-seq data.Based on the trajectory information, GeneRhythm can derive time information (Gene expression chagnes on the trajectory pesodu-time path)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "f95cc183",
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset = 'mouse_embryo_blood'\n",
    "mtx = './dataset/mouse_embryo_blood/counts_5k_final.mtx'\n",
    "barcode = './dataset/mouse_embryo_blood/cell_meta_5kgenes_final.csv'\n",
    "gene  = './dataset/mouse_embryo_blood/gene_meta_5kgenes_final.csv'\n",
    "subprocess.run([\"Rscript\", \"trajectory_inference.R\", dataset, mtx， barcode, gene])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f9ae3d69",
   "metadata": {},
   "source": [
    "##  Frequency information generation\n",
    "In this step, we harness the power of wavelet transformation to extract detailed frequency information from the gene expression data. By leveraging the trajectory information obtained from Monocle3—which orders cells along a pseudotime axis—we can capture both the temporal progression and the underlying periodic patterns of gene expression.\n",
    "\n",
    "Wavelet transformation decomposes the gene expression profiles into various frequency components, enabling us to detect subtle oscillations and rhythmic behaviors that are often not apparent in the time domain alone. This multi-scale analysis helps reveal hidden periodicities and enriches our understanding of gene regulatory mechanisms.\n",
    "\n",
    "By integrating the frequency-domain features with the temporal trajectory and expression, we achieve a more nuanced analysis. The frequency information complements the time-domain data, enhancing gene clustering. Ultimately, this combined approach provides a comprehensive view of the dynamic changes in gene expression, paving the way for deeper insights into cellular functions and regulatory processes.\n",
    "\n",
    "In addition, we implemented several companion functions to support trajectory inputs from different upstream tools while maintaining a unified downstream workflow. Specifically, `frequency_extract_format` reformats trajectory information from different input types into a standardized trajectory table for downstream frequency extraction, requiring pseudotime information and, depending on the input type, optional path labels, cell identifiers, gene identifiers, and expression values. `frequency_extract_scvelo` performs scVelo-based velocity and pseudotime inference and then converts the inferred trajectory into the standard format for frequency feature extraction; `frequency_extract_veloagent` processes VeloAgent-inferred trajectories and reformats them into the same common structure for downstream analysis; and `frequency_extract_celldancer` runs cellDancer-based velocity and pseudotime analysis and converts the resulting trajectories into the standardized format for frequency extraction."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "8dad2426",
   "metadata": {},
   "outputs": [],
   "source": [
    "trajectory_info = pd.read_csv(\"mouse_embryo_blood.csv\")\n",
    "mtx = sc.read_mtx(mtx)\n",
    "mtx = mtx.X.T\n",
    "barcode = pd.read_csv(barcode,sep=',',index_col=0)\n",
    "gene  = pd.read_csv(gene,header=0,index_col = 0)\n",
    "adata = anndata.AnnData(mtx,barcode,gene)\n",
    "frequency_extract(trajectory_info, adata, dataset)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1d86e5d4",
   "metadata": {},
   "source": [
    "# Part 2: Model preparation and training\n",
    "## GCN graph preparation\n",
    "In this phase, we utilize the Mippie PPI database to extract gene-gene interaction information, thereby constructing the graph structure for our Graph Convolutional Network (GCN). Specifically, the database provides gene interaction data that has been validated by both experimental evidence and computational predictions. We treat these interactions as edges in the graph, with each gene represented as a node. By integrating this biologically informed network structure with the previously obtained gene expression and frequency information, the GCN model is better equipped to capture the regulatory relationships and functional synergies between genes. This integration ultimately enhances the accuracy and interpretability of gene clustering and biomarker identification during model training."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c948a441",
   "metadata": {},
   "outputs": [],
   "source": [
    "gene_info = gene\n",
    "for i in range(len(gene_info)):\n",
    "    gene_info.loc[i,\"gene_id\"] = gene_info.loc[i,\"gene_id\"][:18]\n",
    "print(gene_info.head())\n",
    "mg = mygene.MyGeneInfo()\n",
    "gene_id = mg.getgenes(gene_info.loc[:,\"gene_id\"], fields='_id')\n",
    "ids = [gene_id[i].get('_id') for i in range(len(gene_id))]\n",
    "with open(\"mouse_embryo_blood.txt\", 'w') as output:\n",
    "    for row in ids:\n",
    "        output.write(str(row) + '\\n')\n",
    "\n",
    "subprocess.run([\"Rscript\", \"mippie_nc.R\", 'mouse_embryo_blood.txt', 'mippie_subset_blood.tsv'])\n",
    "graph_df = pd.read_csv('mippie_subnet_blood.txt', sep='\\t', header=None)\n",
    "build_graph_mouse(graph_df,gene_info)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce3e444d",
   "metadata": {},
   "source": [
    "## Modle training\n",
    "In this stage, the model is trained using time, frequency, and expression data, along with the previously constructed graph. This integration allows the model to learn a comprehensive latent embedding that encapsulates the intricate relationships among genes. Once the model has been trained, we apply the Leiden algorithm to the latent space to identify gene clusters. These clusters represent groups of genes with similar expression dynamics and regulatory patterns, providing a valuable basis for further biological insights and downstream analysis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "7a4bb271",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "____________________________\n",
      "Start Training VAE...\n",
      "torch.Size([5000, 250])\n",
      "Epochs: 1, AvgLoss: 36.0972\n",
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      "Epochs: 598, AvgLoss: 5.4564\n",
      "torch.Size([5000, 250])\n",
      "Epochs: 599, AvgLoss: 5.4506\n",
      "torch.Size([5000, 250])\n",
      "Epochs: 600, AvgLoss: 5.4511\n",
      "Training for VAE has been done.\n"
     ]
    }
   ],
   "source": [
    "GeneRhythm_Model(input_data = 'mouse_embryo_blood.npy',graph='graph_index.npy',sc_data = adata)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ba19e832",
   "metadata": {},
   "source": [
    "# Part 3: Showing result\n",
    "In this final phase, we visualize the outcomes of our analysis by displaying both the time and frequency information for each identified gene cluster. These visualizations help in interpreting the complex dynamics captured by the model and provide insights into the temporal progression and rhythmicity of gene expression within each cluster."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "04eb68a9",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "show_result(gene_info,trajectory_info)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "726ee70e",
   "metadata": {},
   "source": [
    "Only the first eligible cluster's plots are ploted out. Other clusters's plots are saved to pdf files."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "625dcb6a",
   "metadata": {},
   "source": [
    "Note: As the mouse embryo blood dataset have no comparative data so the function of differential frequency genes/peaks can be found in the other datasets' tutorials. "
   ]
  },
  {
   "attachments": {
    "7db1c2eb-d32e-4282-a5e0-8c785158ff28.png": {
     "image/png": 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    }
   },
   "cell_type": "markdown",
   "id": "476df15e-bbba-4b6e-ad66-a62a3ddf2fd8",
   "metadata": {},
   "source": [
    "# Part 4: Music sonification\n",
    "The generated MusicXML files are automatically saved with show_result function and can be directly opened using MuseScore, enabling visualization of gene-specific rhythmic patterns as standard musical notation.\n",
    "\n",
    "These scores support real-time playback and instrument switching, allowing the same gene rhythm to be rendered with different timbres (e.g., piano) for intuitive auditory comparison. This representation facilitates both visual inspection of rhythmic density and frequency structure, as well as interactive auditory exploration of gene expression dynamics, as demonstrated in the GeneRhythm browser (http://dinglab.rimuhc.ca/generhythm/\n",
    ").![image.png](attachment:7db1c2eb-d32e-4282-a5e0-8c785158ff28.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "487c8959-4646-46ac-850c-ad472624ece2",
   "metadata": {},
   "source": [
    "## Convert the .musicxml to .wav music sound.\n",
    "This step renders the symbolic musical scores encoded in MusicXML format into waveform audio files. Unlike symbolic notation, WAV files provide a continuous acoustic signal that can be directly played, shared, and further analyzed. The conversion enables auditory inspection of gene-specific rhythmic patterns and facilitates downstream signal-based analyses such as spectral characterization, feature extraction, or comparative acoustic evaluation across conditions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "605410d2-7c57-40c3-abc9-39f72992d44f",
   "metadata": {},
   "outputs": [],
   "source": [
    "!powershell -NoProfile -Command \"ls *.musicxml | % { & 'C:\\Program Files\\MuseScore 4\\bin\\MuseScore4.exe' -o ($_.BaseName + '.wav') $_ }\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "78919fd4-6f61-4406-98e0-b2927803e07d",
   "metadata": {},
   "source": [
    "## Convert the .musicxml to .pdf sheet music.\n",
    "This conversion produces publication-ready sheet music layouts, allowing consistent visual interpretation of the symbolic musical encoding. The PDF format ensures software-independent accessibility and facilitates qualitative comparison of rhythmic and melodic patterns across genes and conditions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "6ced1a2f-d429-44a0-912b-a61b6f36e41c",
   "metadata": {},
   "outputs": [],
   "source": [
    "!powershell -NoProfile -Command \"ls *.musicxml | % { & 'C:\\Program Files\\MuseScore 4\\bin\\MuseScore4.exe' -o ($_.BaseName + '.pdf') $_ }\""
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.20"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}