integration

SuperBianC · Jan 6, 2024 · e9b45d0 · e9b45d0
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diff --git a/.gitignore b/.gitignore
@@ -7,7 +7,7 @@ scMulan/.ipynb_checkpoints
 scMulan/utils/__pycache__
 scMulan/reference/GeneSymbolUniform/__pycache__
 scMulan/reference/GeneSymbolUniform/.ipynb_checkpoints
-
+update.sh
 
 # except
 !Data/README.md

diff --git a/Tutorial-integration.ipynb b/Tutorial-integration.ipynb
@@ -13,9 +13,7 @@
    "id": "12f61ec3-f21b-4fce-a652-3172e7b8c7fa",
    "metadata": {},
    "source": [
-    "#### we provide the lung dataset from SCIB (doi.org/10.1038/s41592-021-01336-8)\n",
-    "you can download the sampled dataset from: https://figshare.com/ndownloader/files/24539942\n",
-    "/nfs/public/cell_gpt_data/Intergation_Data/Lung/Lung_atlas_public.h5ad"
+    "#### we use the lung dataset (https://figshare.com/ndownloader/files/24539942) in SCIB (doi.org/10.1038/s41592-021-01336-8)"
    ]
   },
   {
@@ -62,44 +60,9 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "id": "f2116c92-e174-4088-a5fe-76858c51740e",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "adata_path = '/nfs/public/cell_gpt_data/Intergation_Data/Lung/Lung_atlas_public.h5ad' # the data path"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "id": "b306ffe4-7aae-4d3b-ac2e-647b90bbd8d0",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "adata = sc.read_h5ad(adata_path)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 31,
    "id": "3cef709f-7c25-4219-96f6-30df9268b2e6",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "ead734f1869e44f78dcfacccf1a9f19d",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "  0%|          | 0.00/972M [00:00<?, ?B/s]"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "adata = sc.read(\n",
     "    \"Data/lung_atlas.h5ad\",\n",
@@ -109,31 +72,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
-   "id": "37bbc683-8287-48eb-9bec-deae69c579a0",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "AnnData object with n_obs × n_vars = 32472 × 15148\n",
-       "    obs: 'dataset', 'location', 'nGene', 'nUMI', 'patientGroup', 'percent.mito', 'protocol', 'sanger_type', 'size_factors', 'sampling_method', 'batch', 'cell_type', 'donor'\n",
-       "    layers: 'counts'"
-      ]
-     },
-     "execution_count": 32,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "adata"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "id": "1996cf88-0d43-4abd-92c7-eb7d850ded79",
+   "execution_count": 5,
+   "id": "69e0cab9-3c9a-47b7-98b5-1348537c46c8",
    "metadata": {},
    "outputs": [
     {
@@ -144,7 +84,7 @@
        "    layers: 'counts'"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -163,7 +103,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
    "id": "90c52bec-48bc-407c-b049-84cf80139ca2",
    "metadata": {},
    "outputs": [
@@ -180,7 +120,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Processing: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 15148/15148 [00:12<00:00, 1250.63it/s]"
+      "Processing: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 15148/15148 [00:12<00:00, 1238.62it/s]\n"
      ]
     },
     {
@@ -194,23 +134,22 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "\n",
-      "Processing: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 13972/13972 [00:09<00:00, 1505.76it/s]\n"
+      "Processing: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 13972/13972 [00:07<00:00, 1758.63it/s]\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "Shape of output data is (32472, 42117). It should have 42117 genes with cell number unchanged.\n",
-      "h5ad file saved in:/nfs/public/chenyx/scMulan_test/uniformed_adata/lung_uniformed.h5ad\n",
-      "report file saved in: /nfs/public/chenyx/scMulan_test/uniformed_adata/lung_report.csv\n"
+      "h5ad file saved in:/home/bianhaiyang/projects/cellgpt_v1/tools/scMulan_package/Data/lung_uniformed.h5ad\n",
+      "report file saved in: /home/bianhaiyang/projects/cellgpt_v1/tools/scMulan_package/Data/lung_report.csv\n"
      ]
     }
    ],
    "source": [
     "adata_GS_uniformed = GeneSymbolUniform(input_adata=adata,\n",
-    "                                 output_dir=\"/nfs/public/chenyx/scMulan_test/uniformed_adata/\",\n",
+    "                                 output_dir=\"Data/\",\n",
     "                                 output_prefix='lung')"
    ]
   },
@@ -231,7 +170,7 @@
    "source": [
     "## you can read the saved uniformed adata\n",
     "\n",
-    "#adata_GS_uniformed=sc.read_h5ad('/nfs/public/chenyx/scMulan_test/uniformed_adata/liver_uniformed.h5ad')"
+    "#adata_GS_uniformed=sc.read_h5ad('Data/lung_uniformed.h5ad')"
    ]
   },
   {
@@ -263,7 +202,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# norm and log1p count matrix\n",
+    "# norm and log1p, if adata is count matrix\n",
     "if adata_GS_uniformed.X.max() > 10:\n",
     "    sc.pp.normalize_total(adata_GS_uniformed, target_sum=1e4) \n",
     "    sc.pp.log1p(adata_GS_uniformed)"