{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# HPAP107 scRNA-seq and CODEX Integration (with cell type annotations)\n", "\n", "Overview\n", "\n", "This tutorial demonstrates how to integrate HPAP107 scRNA-seq and CODEX datasets from human pancreas using CelLink when cell-type annotations are available.\n", "\n", "Outline\n", "1. Data input\n", "2. Data preprocessing\n", "3. Cellink object construction and alignment\n", "4. Feature imputation and cell-type matching\n", "5. Visualization" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", "from scipy.io import mmread\n", "\n", "import matplotlib.pyplot as plt\n", "plt.rcParams[\"figure.figsize\"] = (6, 4)\n", "\n", "from sklearn.metrics import confusion_matrix, ConfusionMatrixDisplay\n", "\n", "import anndata as ad\n", "import scanpy as sc\n", "\n", "from sklearn.utils.extmath import randomized_svd\n", "from scipy.sparse.linalg import svds\n", "from matplotlib.ticker import MaxNLocator\n", "from matplotlib.lines import Line2D\n", "from sklearn.metrics.pairwise import cosine_similarity\n", "import umap\n", "\n", "import seaborn as sns\n", "\n", "from cellink import Cellink\n", "\n", "import requests\n", "import os\n", "import zipfile" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## DATA input\n", "\n", "Download or point to preprocessed AnnData files. The example cells below download the HPAP107 archive and load four AnnData objects: full scRNA, filtered CODEX, and the two shared-feature objects used for alignment.\n", "\n", "If using your own data, ensure each AnnData contains `.X`, `.obs` with a `cell_type` column, and for CODEX `.obsm['spatial']` if you want spatial plots." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "download success\n", "unzipped data in: unzipped_HPAP107_data\n" ] } ], "source": [ "#download HPAP107 data\n", "dropbox_url = \"https://www.dropbox.com/scl/fo/pnzya149wk2uq7ak4yvej/ADsoD-Hz0s1BGBrAco-w3lU?rlkey=101pdmutrilndv2j4jxa2n5w9&e=1&st=rxntw6f0&dl=1\"\n", "response = requests.get(dropbox_url)\n", "with open(\"HPAP107_data.zip\", \"wb\") as f:\n", " f.write(response.content)\n", "\n", "print(\"download success\")\n", "\n", "extract_dir = \"unzipped_HPAP107_data\"\n", "os.makedirs(extract_dir, exist_ok=True)\n", "\n", "with zipfile.ZipFile(\"HPAP107_data.zip\", 'r') as zip_ref:\n", " zip_ref.extractall(extract_dir)\n", "\n", "print(\"unzipped data in:\", extract_dir)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Data preprocessing\n", "\n", "This notebook uses the provided `cell_type` annotations. Verify the column exists in each AnnData (`combined_adata`, `protein_adata_filter`, `rna_shared`, `protein_shared`) before running the downstream evaluation and matching steps. If `cell_type` is missing, either add appropriate annotations or follow the \"without cell type annotations\" tutorial.\n" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/nfs/turbo/umms-drjieliu/usr/zchx/conda_envs/scarches/lib/python3.10/site-packages/anndata/_core/anndata.py:1908: UserWarning: Variable names are not unique. To make them unique, call `.var_names_make_unique`.\n", " utils.warn_names_duplicates(\"var\")\n", "/nfs/turbo/umms-drjieliu/usr/zchx/conda_envs/scarches/lib/python3.10/site-packages/anndata/_core/anndata.py:1908: UserWarning: Variable names are not unique. To make them unique, call `.var_names_make_unique`.\n", " utils.warn_names_duplicates(\"var\")\n" ] } ], "source": [ "# Load AnnData objects for the preprocessed datasets and datasets with shared features in two modalities\n", "combined_adata = sc.read_h5ad('unzipped_HPAP107_data/pancreas/combined_adata.h5ad')\n", "protein_adata_filter = sc.read_h5ad('unzipped_HPAP107_data/pancreas/protein_adata_filter.h5ad')\n", "rna_shared = sc.read_h5ad('unzipped_HPAP107_data/pancreas/rna_shared.h5ad')\n", "protein_shared = sc.read_h5ad('unzipped_HPAP107_data/pancreas/protein_shared.h5ad')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Cellink object construction and alignment\n", "\n", "Create a `Cellink` instance with full and shared AnnData objects, and optionally split data into batches for efficient processing. Below we show the alignment call with recommended parameter guidance." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Cell annotations are provided. Perform Iteratively OT!\n", "The first modality is split into 1 batches, and max batch size is 5141.\n", "The second modality is split into 5 batches, and max batch size is 4000.\n", "Batch to batch correspondence is:\n", " ['0<->0', '0<->1', '0<->2', '0<->3', '0<->4'].\n" ] } ], "source": [ "arr = [rna_shared, protein_shared]\n", "cellink = Cellink(full_ann1 = combined_adata, full_ann2 = protein_adata_filter, shared_ann1 = rna_shared, shared_ann2 = protein_shared)\n", "cellink.split_into_batches(arr, 4000, seed = 100)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Alignment key parameters and tuning guidance (with cell-type annotations)\n", "\n", "- wt1, wt2: Graph smoothing shrinkage weights applied during the graph smoothing step. The smoothing result is computed as: wt * original_features + (1 - wt) * neighborhood_average. These weights control the relative importance of the center cell vs. neighborhood information. Typical values to try: 0.3, 0.5, 0.7, 1. Use lower wt (more smoothing) when data are noisy; use wt=1 to disable smoothing.You can try all of them to figure out which one is best.\n", "\n", "- n_neighbors (K_Neighbourhood): Number of nearest neighbors used to build the KNN graph. The source code accepts this parameter when constructing graphs. Suggested defaults: 10 (recommended) or 15 for larger datasets. For very small datasets, use 5.\n", "\n", "- reg: Entropic regularization coefficient used in unbalanced OT Sinkhorn. Controls the smoothness and effective sparsity of the transport matrix. Larger reg lead to smoother (less sparse) transport; smaller reg lead to sharper (more sparse) transport. Default: 0.01. Be cautious when setting drastically different reg values across modalities, as it may bias rows/columns to dominate.\n", "\n", "- lambd: Entropic regularization coefficient used in balanced OT. It controls the overall transport loss and numerical behaviour. Setting lambd too low can harm convergence and lead to a drop in alignment accuracy. Default 0.01; change gradually and monitor convergence.\n", "\n", "- sparse: When True, CelLink uses an LBFGS-based solver designed to produce sparser (near one-to-one) correspondences. This often yields crisper matches but is slower and can be numerically less stable on some datasets. When `sparse=False`, Sinkhorn-based dense solvers are used.\n", "\n", "- iterative (bool) and numItermax: With `iterative=True`, CelLink runs the iterative unbalanced OT refinement stage (Stage II). When cell-type annotations are available, iterative refinement is recommended because the algorithm can leverage annotations to improve matching consistency across cell types. `numItermax` controls the Sinkhorn/LBFGS maximum iterations — increase it (for example to 1000 or more) if the solver emits convergence warnings.\n", "\n", "- reg_m (tuple): KL-divergence mass regularization coefficients used by unbalanced Sinkhorn; tune when necessary to control mass deviation between modalities.\n" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Now at batch 0<->0...\n", "4618 cells from Modality X are unmatched in Phase I and are realigned in Phase II.\n", "iterative unbalanced optimal transport converges after 5 iterations with cell-type matching accuracy 96.21%! \n", "\n", "There are 195 unmatched samples and 4946 matched samples in data1!\n", "\n", "3501 cells from Modality Y are unmatched in Phase I and are realigned in Phase II.\n", "iterative unbalanced optimal transport converges after 4 iterations with cell-type matching accuracy 91.35%! \n", "\n", "There are 346 unmatched samples and 3654 matched samples in data2!\n", "\n", "Now at batch 0<->1...\n", "4623 cells from Modality X are unmatched in Phase I and are realigned in Phase II.\n", "iterative unbalanced optimal transport converges after 5 iterations with cell-type matching accuracy 93.97%! \n", "\n", "There are 310 unmatched samples and 4831 matched samples in data1!\n", "\n", "3470 cells from Modality Y are unmatched in Phase I and are realigned in Phase II.\n", "iterative unbalanced optimal transport converges after 4 iterations with cell-type matching accuracy 91.25%! \n", "\n", "There are 350 unmatched samples and 3650 matched samples in data2!\n", "\n", "Now at batch 0<->2...\n", "4648 cells from Modality X are unmatched in Phase I and are realigned in Phase II.\n", "iterative unbalanced optimal transport converges after 5 iterations with cell-type matching accuracy 96.48%! \n", "\n", "There are 181 unmatched samples and 4960 matched samples in data1!\n", "\n", "3523 cells from Modality Y are unmatched in Phase I and are realigned in Phase II.\n", "iterative unbalanced optimal transport converges after 4 iterations with cell-type matching accuracy 90.95%! \n", "\n", "There are 362 unmatched samples and 3638 matched samples in data2!\n", "\n", "Now at batch 0<->3...\n", "4620 cells from Modality X are unmatched in Phase I and are realigned in Phase II.\n", "iterative unbalanced optimal transport converges after 5 iterations with cell-type matching accuracy 98.0%! \n", "\n", "There are 103 unmatched samples and 5038 matched samples in data1!\n", "\n", "3472 cells from Modality Y are unmatched in Phase I and are realigned in Phase II.\n", "iterative unbalanced optimal transport converges after 4 iterations with cell-type matching accuracy 90.86999999999999%! \n", "\n", "There are 365 unmatched samples and 3635 matched samples in data2!\n", "\n", "Now at batch 0<->4...\n", "4592 cells from Modality X are unmatched in Phase I and are realigned in Phase II.\n", "iterative unbalanced optimal transport converges after 6 iterations with cell-type matching accuracy 95.30999999999999%! \n", "\n", "There are 241 unmatched samples and 4900 matched samples in data1!\n", "\n", "3465 cells from Modality Y are unmatched in Phase I and are realigned in Phase II.\n", "iterative unbalanced optimal transport converges after 4 iterations with cell-type matching accuracy 91.33%! \n", "\n", "There are 347 unmatched samples and 3653 matched samples in data2!\n", "\n" ] } ], "source": [ "cellink.alignment(wt1 = 0.5, wt2 = 0.5, n_neighbors=10,\n", " reg = 0.01, lambd = 0.01, reg_m1 = (20, 0.01), reg_m2 = (0.01, 20), numItermax = 1000, iterative=True, sparse = False)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Feature imputation and cell-type matching\n", "\n", "After alignment, learned transport maps are used to impute cross-modal features and to predict cell types by aggregating transport mass to annotation classes. " ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "rna_source_ct_array = np.zeros(shape = rna_shared.shape[0], dtype = 'object')\n", "rna_predict_ct_array = np.zeros(shape = rna_shared.shape[0], dtype = 'object')\n", "# the cell index of the rna_aligned_protein is not the same as the original cell index, modify the logic by looping cellink.partition1[i] rather than len(rna_batch)\n", "rna_aligned_protein = np.zeros(shape = (combined_adata.shape[0], protein_adata_filter.shape[1]))\n", "for i in range(len(cellink.partition1)):\n", " cell_id = cellink.partition1[i]\n", " match_id = np.array(list(cellink.cell_correspondence_partition1[i].keys()))\n", " jump_num = 0\n", " for j in range(len(cell_id)):\n", " rna_source_ct_array[cell_id[j]] = rna_shared.obs['cell_type'].iloc[cell_id[j]]\n", " unmatched_cell_id_rna = cellink.arr1_unmatched_cell_id[i]\n", " if j in unmatched_cell_id_rna:\n", " rna_predict_ct_array[cell_id[j]] = cellink.arr1_wrong_ct[i][np.where(unmatched_cell_id_rna == j)[0][0]]\n", " jump_num = jump_num + 1\n", " else:\n", " rna_predict_ct_array[cell_id[j]] = rna_shared.obs['cell_type'].iloc[cell_id[j]]\n", " nid = np.where(match_id == j)[0][0]\n", " rna_aligned_protein[cell_id[j], :] = cellink.feature_imputation_partition1[i][nid, :]\n", "\n", "protein_source_ct_array = np.zeros(shape = protein_shared.shape[0], dtype = 'object')\n", "protein_predict_ct_array = np.zeros(shape = protein_shared.shape[0], dtype = 'object')\n", "protein_aligned_rna = np.zeros(shape = (protein_adata_filter.shape[0], combined_adata.shape[1]))\n", "for i in range(len(cellink.partition2)):\n", " cell_id = cellink.partition2[i]\n", " match_id = np.array(list(cellink.cell_correspondence_partition2[i].keys()))\n", " jump_num = 0\n", " for j in range(len(cell_id)):\n", " protein_source_ct_array[cell_id[j]] = protein_shared.obs['cell_type'].iloc[cell_id[j]]\n", " unmatched_cell_id_protein = cellink.arr2_unmatched_cell_id[i]\n", " if j in unmatched_cell_id_protein:\n", " protein_predict_ct_array[cell_id[j]] = cellink.arr2_wrong_ct[i][np.where(unmatched_cell_id_protein == j)[0][0]]\n", " jump_num += 1\n", " else:\n", " protein_predict_ct_array[cell_id[j]] = protein_shared.obs['cell_type'].iloc[cell_id[j]]\n", " nid = np.where(match_id == j)[0][0]\n", " protein_aligned_rna[cell_id[j], :] = cellink.feature_imputation_partition2[i][nid, :]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Visualization\n", "\n", "Compute UMAPs and produce embedding panels and confusion matrices to evaluate alignment quality and cell-type matching." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "import umap\n", "matched_rna = rna_source_ct_array == rna_predict_ct_array\n", "matched_protein = protein_source_ct_array == protein_predict_ct_array\n", "dataall_0 = np.concatenate([combined_adata.X, protein_aligned_rna[matched_protein, :]], axis = 0)\n", "embedding_0 = umap.UMAP(n_components=2, n_epochs = 500, n_neighbors = 15, random_state = 30, min_dist = 0.5).fit_transform(dataall_0)\n", "ct_array_double_0 = np.concatenate([rna_source_ct_array, protein_source_ct_array[protein_source_ct_array == protein_predict_ct_array]], axis = 0)\n", "\n", "dataall_1 = np.concatenate([protein_adata_filter.X, rna_aligned_protein[matched_rna, :]], axis = 0)\n", "embedding_1 = umap.UMAP(n_components=2, n_epochs = 500, n_neighbors = 15, random_state = 30, min_dist = 0.5).fit_transform(dataall_1)\n", "ct_array_double_1 = np.concatenate([protein_source_ct_array, rna_source_ct_array[rna_source_ct_array == rna_predict_ct_array]], axis = 0)\n", "\n", "scrna_all = np.concatenate([combined_adata[matched_rna].X, rna_aligned_protein[matched_rna]], axis = 1)\n", "codex_all = np.concatenate([protein_aligned_rna[matched_protein], protein_adata_filter[matched_protein].X], axis = 1)\n", "\n", "dataall_2 = np.concatenate([scrna_all, codex_all], axis = 0)\n", "embedding_2 = umap.UMAP(n_components=2, n_epochs = 500, n_neighbors = 15, random_state = 30, min_dist = 0.5).fit_transform(dataall_2)\n", "ct_array_double_2 = np.concatenate([rna_source_ct_array[matched_rna], protein_source_ct_array[matched_protein]], axis = 0)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "protein_aligned_rna = protein_aligned_rna[protein_source_ct_array == protein_predict_ct_array, :]\n", "ct_protein_aligned = protein_source_ct_array[protein_source_ct_array == protein_predict_ct_array]\n", "rna_aligned_protein = rna_aligned_protein[rna_source_ct_array == rna_predict_ct_array, :]\n", "ct_rna_aligned = rna_source_ct_array[rna_source_ct_array == rna_predict_ct_array]" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "from matplotlib.lines import Line2D\n", "import matplotlib.pyplot as plt\n", "datatype = ['scRNA', 'CODEX']\n", "ct_array_double = ct_array_double_2\n", "datatype_array_double = np.concatenate([np.repeat(datatype[0], sum(matched_rna)), np.repeat(datatype[1], sum(matched_protein))], axis = 0)\n", "ct_array1 = combined_adata[matched_rna,].obs['cell_type'].values\n", "ct_array2 = protein_adata_filter[matched_protein].obs['cell_type'].values \n", "\n", "color_palette = plt.cm.tab10(np.linspace(0, 1, 10))[::-1]\n", "cts = np.unique(ct_array_double)\n", "num_type = len(cts)\n", "if num_type > 10:\n", " repeats = -(-num_type // 10)\n", " color_palettes = np.tile(color_palette, (repeats, 1))\n", " colors = color_palettes[:num_type]\n", "else:\n", " colors = color_palette[:num_type]\n", "colorbar = {t: colors[i] for i, t in enumerate(cts)}\n", "\n", "manual_colors = ['#F26B78', '#7995CC', '#F4E41E']\n", "for i, color in enumerate(manual_colors):\n", " if i < len(cts):\n", " colorbar[cts[i]] = np.array([int(color.strip('#')[j:j+2], 16) / 256 for j in (0, 2, 4)] + [1]) # Convert hex to RGB tuple\n", "\n", "if len(cts) >= 4:\n", " colorbar[cts[3]] = (0, 0.6, 0.2, 1.0)\n", " \n", "color_points = np.array([colorbar[i] for i in ct_array_double])\n", "\n", "dts = np.unique(datatype_array_double)\n", "color_datatype = [\"#FFA500\", \"#004D99\"]\n", "colorbardt = {t: color_datatype[i] for i, t in enumerate(dts)}\n", "color_dt = np.array([colorbardt[i] for i in datatype_array_double])\n", "\n", "grey = np.array([0.9, 0.9, 0.9, 0.2])[np.newaxis, :]\n", "\n", "protein_id = np.array(range(0, len(ct_array1)))\n", "rna_id = np.array(range(len(ct_array1), len(ct_array_double)))\n", "color_points1 = color_points.copy()\n", "color_points1[rna_id, :] = grey\n", "color_points2 = color_points.copy()\n", "color_points2[protein_id, :] = grey\n", "\n", "fig, axs = plt.subplots(1, 2, figsize=(12, 6))\n", "axs[0].scatter(embedding_2[:,0], embedding_2[:,1], color=color_points1, s=5.)\n", "axs[1].scatter(embedding_2[:,0], embedding_2[:,1], color=color_points2, s=5.)\n", "axs[0].set_title('scRNA highlighted Embeddings')\n", "axs[1].set_title('CODEX highlighted Embeddings')\n", "axs[0].set_xlabel('UMAP-1')\n", "axs[0].set_ylabel('UMAP-2')\n", "axs[1].set_xlabel('UMAP-1')\n", "axs[1].set_ylabel('UMAP-2')\n", "for i in axs:\n", " i.set_facecolor('none')\n", "fig.patch.set_facecolor('none')\n", "\n", "legend_celltype = [Line2D([0], [0], marker='o', color='w', label=f'{t}',\n", " markerfacecolor=c, markersize=10) for t, c in colorbar.items()]\n", "legend_dt = [Line2D([0], [0], marker='o', color='w', label=f'{t}',\n", " markerfacecolor=c, markersize=10) for t, c in colorbardt.items()]\n", "\n", "axs[0].legend(handles = legend_celltype, title = \"Cell Types\", loc = \"lower right\")\n", "#plt.gca().add_artist(legend1)\n", "axs[1].legend(handles = legend_celltype, title = \"Cell Types\", loc = \"lower right\")\n", "\n", "\n", "plt.show()\n" ] } ], "metadata": { "kernelspec": { "display_name": "alignment", "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": "3.10.13" }, "orig_nbformat": 4 }, "nbformat": 4, "nbformat_minor": 2 }