Update docs/BIOI611_analysis_10x_dataset_PBMC.ipynb

Bix4UMD · Nov 14, 2024 · 722582b · 722582b
1 parent 8aa64d5
commit 722582b
Showing 1 changed file with 35 additions and 34 deletions.
diff --git a/docs/BIOI611_analysis_10x_dataset_PBMC.ipynb b/docs/BIOI611_analysis_10x_dataset_PBMC.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "204f3bad",
+   "id": "7361b872",
    "metadata": {},
    "source": [
     "# \n",
@@ -13,7 +13,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ace9024e",
+   "id": "c4fa7fad",
    "metadata": {},
    "source": [
     "You can download the data from the link [here](https://www.10xgenomics.com/datasets/5k-human-pbmcs-3-v3-1-chromium-controller-3-1-standard)\n",
@@ -30,7 +30,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "7cf9854c",
+   "id": "bc62b984",
    "metadata": {},
    "outputs": [
     {
@@ -51,7 +51,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b01eb439",
+   "id": "d768fb8e",
    "metadata": {},
    "source": [
     "### Check R1 and R2"
@@ -64,7 +64,7 @@
     }
    },
    "cell_type": "markdown",
-   "id": "91bd1990",
+   "id": "93ced0e1",
    "metadata": {},
    "source": [
     "\n",
@@ -90,18 +90,10 @@
     "3. Accurate Quantification: Using UMIs allows for a more accurate measure of gene expression by avoiding overcounting due to PCR duplicates, providing a closer representation of the actual RNA molecules present in each cell.\n"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "10631a7c",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
   {
    "cell_type": "code",
    "execution_count": 4,
-   "id": "51642c85",
+   "id": "1b9347d3",
    "metadata": {},
    "outputs": [
     {
@@ -131,7 +123,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "id": "2634e3a3",
+   "id": "844e16f8",
    "metadata": {},
    "outputs": [
     {
@@ -160,15 +152,15 @@
   },
   {
    "cell_type": "markdown",
-   "id": "56b412e0",
+   "id": "5114bfd7",
    "metadata": {},
    "source": [
     "## Run Cellranger \n"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "a47ca1d0",
+   "id": "25fe6349",
    "metadata": {},
    "source": [
     "Cell Ranger is a software suite developed by 10x Genomics for processing and analyzing data from their single-cell RNA-seq (scRNA-seq), single-cell ATAC-seq (scATAC-seq), and other single-cell assays. Cell Ranger performs tasks such as alignment, filtering, UMI counting, and data aggregation, streamlining the analysis of single-cell datasets generated by 10x Genomics platforms.\n",
@@ -188,7 +180,7 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "94baac4d",
+   "id": "accac6bc",
    "metadata": {},
    "outputs": [
     {
@@ -207,7 +199,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "8e0d8a71",
+   "id": "51f9add6",
    "metadata": {},
    "outputs": [
     {
@@ -249,7 +241,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "aa83ff95",
+   "id": "f95c5fba",
    "metadata": {},
    "source": [
     "Input files/folder for `cellranger count`:\n",
@@ -265,7 +257,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "id": "398d638c",
+   "id": "e50a0d91",
    "metadata": {},
    "outputs": [
     {
@@ -325,15 +317,15 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ed0afa1c",
+   "id": "f498c3e5",
    "metadata": {},
    "source": [
     "### Output folder"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "57f2c4f7",
+   "id": "e7d25d36",
    "metadata": {},
    "source": [
     "The job you submitted will generate an output folder: \n"
@@ -342,7 +334,7 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "id": "12402f25",
+   "id": "2bcc20e3",
    "metadata": {},
    "outputs": [
     {
@@ -399,7 +391,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b2521ba6",
+   "id": "a7e24143",
    "metadata": {},
    "source": [
     "You can also find a copy here:\n",
@@ -411,7 +403,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5a937661",
+   "id": "8dbc5def",
    "metadata": {},
    "source": [
     "The summary file in html format is the first file you will check:\n",
@@ -427,7 +419,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "193aedaa",
+   "id": "2bdd8c5a",
    "metadata": {},
    "source": [
     "The three files below are usually used as input for downstream analysis. "
@@ -436,7 +428,7 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "id": "a095fdce",
+   "id": "4133bfb6",
    "metadata": {},
    "outputs": [
     {
@@ -455,11 +447,9 @@
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "58e56047",
+   "cell_type": "markdown",
+   "id": "073a544c",
    "metadata": {},
-   "outputs": [],
    "source": [
     "The folder above contains only detected cell-associated\n",
     "barcodes. Each element of the matrix is the\n",
@@ -474,13 +464,24 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d95bba5d",
+   "id": "d211706c",
    "metadata": {},
    "source": [
     "## Reference\n",
     "\n",
-    "https://teichlab.github.io/scg_lib_structs/methods_html/10xChromium3.html\n"
+    "https://teichlab.github.io/scg_lib_structs/methods_html/10xChromium3.html\n",
+    "\n",
+    "https://bioinformatics.ccr.cancer.gov/docs/getting-started-with-scrna-seq/2024-04-17_KimiaDadkhah.pdf\n",
+    "\n"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6da687e3",
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {