Skip to content

Commit

Permalink
Revert "update tutorial with new download instructions"
Browse files Browse the repository at this point in the history
This reverts commit 70aa20c.
  • Loading branch information
katosh committed Aug 21, 2024
1 parent 70aa20c commit 3a53aeb
Showing 1 changed file with 21 additions and 229 deletions.
250 changes: 21 additions & 229 deletions notebooks/basic_tutorial.ipynb
Original file line number Diff line number Diff line change
Expand Up @@ -30,11 +30,11 @@
"id": "8c279d2b-9918-4de1-a584-fba1ff727eff",
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-12T08:31:32.475976Z",
"iopub.status.busy": "2024-08-12T08:31:32.475401Z",
"iopub.status.idle": "2024-08-12T08:33:39.343753Z",
"shell.execute_reply": "2024-08-12T08:33:39.342235Z",
"shell.execute_reply.started": "2024-08-12T08:31:32.475928Z"
"iopub.execute_input": "2023-07-09T15:15:01.801561Z",
"iopub.status.busy": "2023-07-09T15:15:01.801285Z",
"iopub.status.idle": "2023-07-09T15:15:06.333926Z",
"shell.execute_reply": "2023-07-09T15:15:06.332609Z",
"shell.execute_reply.started": "2023-07-09T15:15:01.801533Z"
},
"tags": []
},
Expand Down Expand Up @@ -79,11 +79,11 @@
"id": "975d3714-65c5-42d5-8a83-192aa26b36fa",
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-12T08:33:39.347232Z",
"iopub.status.busy": "2024-08-12T08:33:39.345904Z",
"iopub.status.idle": "2024-08-12T08:33:39.856647Z",
"shell.execute_reply": "2024-08-12T08:33:39.855445Z",
"shell.execute_reply.started": "2024-08-12T08:33:39.347188Z"
"iopub.execute_input": "2023-07-09T15:15:06.336658Z",
"iopub.status.busy": "2023-07-09T15:15:06.335919Z",
"iopub.status.idle": "2023-07-09T15:15:06.350385Z",
"shell.execute_reply": "2023-07-09T15:15:06.349663Z",
"shell.execute_reply.started": "2023-07-09T15:15:06.336628Z"
},
"tags": []
},
Expand All @@ -108,34 +108,20 @@
"source": [
"## Step 1: Reading and Displaying the Dataset\n",
"\n",
"We will start by loading the sc## Step 1: Reading and Displaying the Dataset\n",
"\n",
"We will start by loading the scRNA-seq dataset. For this demonstration, we will use the preprocessed T-cell depleted bone marrow data as described in the Mellon manuscript.\n",
"\n",
"### Download the Dataset\n",
"\n",
"First, download the dataset manually from the following Google Drive link:\n",
"\n",
"[Download preprocessed T-cell depleted bone marrow dataset](https://drive.google.com/uc?export=download&id=1eW79vxKafjNqOyRM6r0ocgnGwgN630CQ)\n",
"\n",
"After clicking the link, you may encounter a warning about the file size being too large for Google to scan for viruses. Click **Download anyway** to proceed with the download.\n",
"\n",
"### Load the Dataset\n",
"\n",
"Once downloaded, place the file in the `data/` directory of your project. Now, you can load the dataset using the following Python code:"
"We will start by loading the scRNA-seq dataset. For this demonstration, we will use the preprocessed T-cell depleted bone marrow data as described in the Mellon manuscript."
]
},
{
"cell_type": "code",
"execution_count": 6,
"execution_count": 3,
"id": "1e337a5b-6301-4bdf-b7fe-09d618814bee",
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-12T09:31:38.000613Z",
"iopub.status.busy": "2024-08-12T09:31:38.000120Z",
"iopub.status.idle": "2024-08-12T09:31:49.169864Z",
"shell.execute_reply": "2024-08-12T09:31:49.168790Z",
"shell.execute_reply.started": "2024-08-12T09:31:38.000571Z"
"iopub.execute_input": "2023-07-09T15:15:06.351555Z",
"iopub.status.busy": "2023-07-09T15:15:06.351329Z",
"iopub.status.idle": "2023-07-09T15:15:13.935314Z",
"shell.execute_reply": "2023-07-09T15:15:13.934232Z",
"shell.execute_reply.started": "2023-07-09T15:15:06.351534Z"
},
"tags": []
},
Expand All @@ -153,13 +139,14 @@
" obsp: 'DM_Kernel', 'DM_Similarity', 'connectivities', 'distances', 'knn'"
]
},
"execution_count": 6,
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ad = sc.read(\"data/preprocessed_t-cell-depleted-bm-rna.h5ad\")\n",
"ad_url = \"https://fh-pi-setty-m-eco-public.s3.amazonaws.com/mellon-tutorial/preprocessed_t-cell-depleted-bm-rna.h5ad\"\n",
"ad = sc.read(\"data/preprocessed_t-cell-depleted-bm-rna.h5ad\", backup_url=ad_url)\n",
"ad"
]
},
Expand Down Expand Up @@ -1336,202 +1323,7 @@
},
"widgets": {
"application/vnd.jupyter.widget-state+json": {
"state": {
"03812144df4d4d8597774b40e7018352": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "2.0.0",
"model_name": "LayoutModel",
"state": {}
},
"0993c640f5a441b8a87258627d6a24d0": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HTMLStyleModel",
"state": {
"description_width": "",
"font_size": null,
"text_color": null
}
},
"1261ce204eaa4b4699dc1a29ecb6f648": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "ProgressStyleModel",
"state": {
"description_width": ""
}
},
"18453e4ef97b48a39bc9daca66623103": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "2.0.0",
"model_name": "LayoutModel",
"state": {}
},
"19e80f5e007f4b01b9716950198267d9": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HTMLStyleModel",
"state": {
"description_width": "",
"font_size": null,
"text_color": null
}
},
"1d1733b870004a43a8ec4c8820d3adcc": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "FloatProgressModel",
"state": {
"bar_style": "success",
"layout": "IPY_MODEL_2cfe8a7c25ac463aa2d89392b56f91df",
"max": 2452,
"style": "IPY_MODEL_1261ce204eaa4b4699dc1a29ecb6f648",
"value": 2452
}
},
"2c59e024b2b6467792243135f0522e78": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "FloatProgressModel",
"state": {
"bar_style": "success",
"layout": "IPY_MODEL_6327d02af0ce4e519e786b8990b39847",
"max": 2452,
"style": "IPY_MODEL_c59f8a5ee5514b5280041fa770d3cf31",
"value": 2452
}
},
"2cfe8a7c25ac463aa2d89392b56f91df": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "2.0.0",
"model_name": "LayoutModel",
"state": {}
},
"36e3e24b48c74c64a1bc04f894f631fe": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "2.0.0",
"model_name": "LayoutModel",
"state": {}
},
"3ee1b0ccd230470d91358a08ffca70f0": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "2.0.0",
"model_name": "LayoutModel",
"state": {}
},
"40cb999c076743febca5d5842bd202af": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HTMLModel",
"state": {
"layout": "IPY_MODEL_a2b5bcbbf2de44dba7b93a478e6f8431",
"style": "IPY_MODEL_19e80f5e007f4b01b9716950198267d9",
"value": " 2.39k/2.39k [00:00<00:00, 148kB/s]"
}
},
"495d59ee03d743858f72728737537336": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "2.0.0",
"model_name": "LayoutModel",
"state": {}
},
"6327d02af0ce4e519e786b8990b39847": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "2.0.0",
"model_name": "LayoutModel",
"state": {}
},
"7ecca251ed98456fa6fe21c2dccd347d": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HTMLModel",
"state": {
"layout": "IPY_MODEL_495d59ee03d743858f72728737537336",
"style": "IPY_MODEL_0993c640f5a441b8a87258627d6a24d0",
"value": "100%"
}
},
"960a5e2d14124c0e8819095aa4f53487": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HTMLStyleModel",
"state": {
"description_width": "",
"font_size": null,
"text_color": null
}
},
"a2b5bcbbf2de44dba7b93a478e6f8431": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "2.0.0",
"model_name": "LayoutModel",
"state": {}
},
"b3e4a8e2a30841b7bc5985758d670edc": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HBoxModel",
"state": {
"children": [
"IPY_MODEL_7ecca251ed98456fa6fe21c2dccd347d",
"IPY_MODEL_1d1733b870004a43a8ec4c8820d3adcc",
"IPY_MODEL_fdf72f0db5d74606b2ed4a41cb723f6a"
],
"layout": "IPY_MODEL_3ee1b0ccd230470d91358a08ffca70f0"
}
},
"b772f004474240c089f8d3909d970418": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HTMLModel",
"state": {
"layout": "IPY_MODEL_03812144df4d4d8597774b40e7018352",
"style": "IPY_MODEL_960a5e2d14124c0e8819095aa4f53487",
"value": "100%"
}
},
"c59f8a5ee5514b5280041fa770d3cf31": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "ProgressStyleModel",
"state": {
"description_width": ""
}
},
"d69763ed81294cbea0371a6d4b363f7e": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HBoxModel",
"state": {
"children": [
"IPY_MODEL_b772f004474240c089f8d3909d970418",
"IPY_MODEL_2c59e024b2b6467792243135f0522e78",
"IPY_MODEL_40cb999c076743febca5d5842bd202af"
],
"layout": "IPY_MODEL_36e3e24b48c74c64a1bc04f894f631fe"
}
},
"fdf72f0db5d74606b2ed4a41cb723f6a": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HTMLModel",
"state": {
"layout": "IPY_MODEL_18453e4ef97b48a39bc9daca66623103",
"style": "IPY_MODEL_ff2c1b45c8634904a204df13c29a0a47",
"value": " 2.39k/2.39k [00:00<00:00, 156kB/s]"
}
},
"ff2c1b45c8634904a204df13c29a0a47": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HTMLStyleModel",
"state": {
"description_width": "",
"font_size": null,
"text_color": null
}
}
},
"state": {},
"version_major": 2,
"version_minor": 0
}
Expand Down

0 comments on commit 3a53aeb

Please sign in to comment.