Skip to content

Commit

Permalink
boxes for surface protein
Browse files Browse the repository at this point in the history
  • Loading branch information
Luis committed Feb 20, 2025
1 parent d11f40d commit e485832
Show file tree
Hide file tree
Showing 6 changed files with 123 additions and 76 deletions.
33 changes: 21 additions & 12 deletions jupyter-book/surface_protein/annotation.ipynb
View file
Original file line number Diff line number Diff line change
Expand Up @@ -2,12 +2,29 @@
"cells": [
{
"cell_type": "markdown",
"id": "7d2eba33",
"id": "78ea0e3b-bae3-4e69-b01a-85364b9ba6bc",
"metadata": {},
"source": [
"``````{admonition} How do I set up an environment with the yml file used in this chapter?\n",
":class: dropdown\n",
"# Annotation\n"
]
},
{
"cell_type": "markdown",
"id": "ab1b9b6e",
"metadata": {},
"source": [
"```{dropdown} <i class=\"fas fa-brain\"></i>&nbsp;&nbsp;&nbsp;Key takeaways\n",
"\n",
":::{card}\n",
":link: surface-protein-annotation-key-takeaway-1\n",
":link-type: ref\n",
"ADT data annotation improves cell identification, especially for immune cells, by complementing RNA data with surface protein markers.\n",
":::\n",
"\n",
"```\n",
"\n",
"\n",
"``````{dropdown} <i class=\"fa-solid fa-gear\"></i>&nbsp;&nbsp;&nbsp;Environment setup\n",
"`````{tab-set}\n",
" \n",
"````{tab-item} Steps\n",
Expand All @@ -22,23 +39,15 @@
"````\n",
"\n",
"`````\n",
"\n",
"``````"
]
},
{
"cell_type": "markdown",
"id": "78ea0e3b-bae3-4e69-b01a-85364b9ba6bc",
"metadata": {},
"source": [
"# Annotation\n"
]
},
{
"cell_type": "markdown",
"id": "a7fc19a8-60ed-4264-b900-b87440f78992",
"metadata": {},
"source": [
"(surface-protein-annotation-key-takeaway-1)=\n",
"## Motivation\n",
"\n",
"Similar to RNA data, it is possible to annotate the ADT data based on surface protein markers.\n",
Expand Down
32 changes: 20 additions & 12 deletions jupyter-book/surface_protein/batch_correction.ipynb
View file
Original file line number Diff line number Diff line change
Expand Up @@ -2,12 +2,28 @@
"cells": [
{
"cell_type": "markdown",
"id": "bc8dc804",
"id": "5a6cd732-e46a-4317-86db-211584a8e888",
"metadata": {},
"source": [
"# Batch correction"
]
},
{
"cell_type": "markdown",
"id": "db558a57",
"metadata": {},
"source": [
"``````{admonition} How do I set up an environment with the yml file used in this chapter?\n",
":class: dropdown\n",
"```{dropdown} <i class=\"fas fa-brain\"></i>&nbsp;&nbsp;&nbsp;Key takeaways\n",
"\n",
":::{card}\n",
":link: surface-protein-batch-correction-key-takeaway-1\n",
":link-type: ref\n",
"Due to pronounced batch effects in ADT data, methods like Harmony or scVI, originally designed for transcriptomics data, are recommended for batch correction, as they effectively integrate samples and maintain cell type separation.\n",
":::\n",
"\n",
"```\n",
"\n",
"``````{dropdown} <i class=\"fa-solid fa-gear\"></i>&nbsp;&nbsp;&nbsp;Environment setup\n",
"`````{tab-set}\n",
" \n",
"````{tab-item} Steps\n",
Expand All @@ -22,23 +38,15 @@
"````\n",
"\n",
"`````\n",
"\n",
"``````"
]
},
{
"cell_type": "markdown",
"id": "5a6cd732-e46a-4317-86db-211584a8e888",
"metadata": {},
"source": [
"# Batch correction"
]
},
{
"cell_type": "markdown",
"id": "ffaa32f5-6882-4b8a-ba2c-a93e77cdd33f",
"metadata": {},
"source": [
"(surface-protein-batch-correction-key-takeaway-1)=\n",
"## Motivation"
]
},
Expand Down
32 changes: 20 additions & 12 deletions jupyter-book/surface_protein/dimensionality_reduction.ipynb
View file
Original file line number Diff line number Diff line change
Expand Up @@ -2,12 +2,28 @@
"cells": [
{
"cell_type": "markdown",
"id": "8ac8e0f0",
"id": "5a6cd732-e46a-4317-86db-211584a8e888",
"metadata": {},
"source": [
"# Dimensionality Reduction"
]
},
{
"cell_type": "markdown",
"id": "84bce38c",
"metadata": {},
"source": [
"``````{admonition} How do I set up an environment with the yml file used in this chapter?\n",
":class: dropdown\n",
"```{dropdown} <i class=\"fas fa-brain\"></i>&nbsp;&nbsp;&nbsp;Key takeaways\n",
"\n",
":::{card}\n",
":link: surface-protein-dimensionality-reduction-key-takeaway-1\n",
":link-type: ref\n",
"Use t-SNE or UMAP for ADT visualization; PCA can help reduce dimensionality in large datasets.\n",
":::\n",
"\n",
"```\n",
"\n",
"``````{dropdown} <i class=\"fa-solid fa-gear\"></i>&nbsp;&nbsp;&nbsp;Environment setup\n",
"`````{tab-set}\n",
" \n",
"````{tab-item} Steps\n",
Expand All @@ -22,23 +38,15 @@
"````\n",
"\n",
"`````\n",
"\n",
"``````"
]
},
{
"cell_type": "markdown",
"id": "5a6cd732-e46a-4317-86db-211584a8e888",
"metadata": {},
"source": [
"# Dimensionality Reduction"
]
},
{
"cell_type": "markdown",
"id": "f946feb9",
"metadata": {},
"source": [
"(surface-protein-dimensionality-reduction-key-takeaway-1)=\n",
"## Motivation"
]
},
Expand Down
32 changes: 20 additions & 12 deletions jupyter-book/surface_protein/doublet_detection.ipynb
View file
Original file line number Diff line number Diff line change
Expand Up @@ -2,12 +2,28 @@
"cells": [
{
"cell_type": "markdown",
"id": "7e6b4b36",
"id": "2dea9174-2c6f-4d0b-9d9d-051840944647",
"metadata": {},
"source": [
"# Doublet detection"
]
},
{
"cell_type": "markdown",
"id": "b9bbf4f1",
"metadata": {},
"source": [
"``````{admonition} How do I set up an environment with the yml file used in this chapter?\n",
":class: dropdown\n",
"```{dropdown} <i class=\"fas fa-brain\"></i>&nbsp;&nbsp;&nbsp;Key takeaways\n",
"\n",
":::{card}\n",
":link: surface-protein-doublet-detection-key-takeaway-1\n",
":link-type: ref\n",
"Heterotypic doublets in ADT data can be identified and removed using mutually exclusive cell type markers (e.g., CD3, CD19, CD14), with cells expressing both markers likely representing doublets.\n",
":::\n",
"\n",
"```\n",
"\n",
"``````{dropdown} <i class=\"fa-solid fa-gear\"></i>&nbsp;&nbsp;&nbsp;Environment setup\n",
"`````{tab-set}\n",
" \n",
"````{tab-item} Steps\n",
Expand All @@ -22,23 +38,15 @@
"````\n",
"\n",
"`````\n",
"\n",
"``````"
]
},
{
"cell_type": "markdown",
"id": "2dea9174-2c6f-4d0b-9d9d-051840944647",
"metadata": {},
"source": [
"# Doublet detection"
]
},
{
"cell_type": "markdown",
"id": "7b28b05c-6ff8-4d7f-8701-3bb8b4969152",
"metadata": {},
"source": [
"(surface-protein-doublet-detection-key-takeaway-1)=\n",
"## Motivation"
]
},
Expand Down
35 changes: 21 additions & 14 deletions jupyter-book/surface_protein/normalization.ipynb
View file
Original file line number Diff line number Diff line change
Expand Up @@ -2,12 +2,28 @@
"cells": [
{
"cell_type": "markdown",
"id": "db78d89c",
"id": "5a6cd732-e46a-4317-86db-211584a8e888",
"metadata": {},
"source": [
"# Normalization"
]
},
{
"cell_type": "markdown",
"id": "855ac3ef",
"metadata": {},
"source": [
"``````{admonition} How do I set up an environment with the yml file used in this chapter?\n",
":class: dropdown\n",
"```{dropdown} <i class=\"fas fa-brain\"></i>&nbsp;&nbsp;&nbsp;Key takeaways\n",
"\n",
":::{card}\n",
":link: surface-protein-normalization-key-takeaway-1\n",
":link-type: ref\n",
"ADT data in CITE-seq requires normalization methods like CLR or DSB to address noise and biases, with DSB removing ambient and technical noise using background controls.\n",
":::\n",
"\n",
"```\n",
"\n",
"``````{dropdown} <i class=\"fa-solid fa-gear\"></i>&nbsp;&nbsp;&nbsp;Environment setup\n",
"`````{tab-set}\n",
" \n",
"````{tab-item} Steps\n",
Expand All @@ -21,24 +37,15 @@
"```\n",
"````\n",
"\n",
"`````\n",
"\n",
"``````"
]
},
{
"cell_type": "markdown",
"id": "5a6cd732-e46a-4317-86db-211584a8e888",
"metadata": {},
"source": [
"# Normalization"
"`````"
]
},
{
"cell_type": "markdown",
"id": "1c6f98c8",
"metadata": {},
"source": [
"(surface-protein-normalization-key-takeaway-1)=\n",
"## Motivation"
]
},
Expand Down
35 changes: 21 additions & 14 deletions jupyter-book/surface_protein/quality_control.ipynb
View file
Original file line number Diff line number Diff line change
Expand Up @@ -2,12 +2,28 @@
"cells": [
{
"cell_type": "markdown",
"id": "02bc17cb",
"id": "5a6cd732-e46a-4317-86db-211584a8e888",
"metadata": {},
"source": [
"# Quality control"
]
},
{
"cell_type": "markdown",
"id": "81309516",
"metadata": {},
"source": [
"``````{admonition} How do I set up an environment with the yml file used in this chapter?\n",
":class: dropdown\n",
"```{dropdown} <i class=\"fas fa-brain\"></i>&nbsp;&nbsp;&nbsp;Key takeaways\n",
"\n",
":::{card}\n",
":link: surface-protein-quality-control-key-takeaway-1\n",
":link-type: ref\n",
"Single-cell protein measurements complement RNA-seq data, improving cell type identification and revealing treatment effects not visible at the transcript level.\n",
":::\n",
"\n",
"```\n",
"\n",
"``````{dropdown} <i class=\"fa-solid fa-gear\"></i>&nbsp;&nbsp;&nbsp;Environment setup\n",
"`````{tab-set}\n",
" \n",
"````{tab-item} Steps\n",
Expand All @@ -21,17 +37,7 @@
"```\n",
"````\n",
"\n",
"`````\n",
"\n",
"``````"
]
},
{
"cell_type": "markdown",
"id": "5a6cd732-e46a-4317-86db-211584a8e888",
"metadata": {},
"source": [
"# Quality control"
"`````"
]
},
{
Expand All @@ -40,6 +46,7 @@
"metadata": {},
"source": [
"(surface-protein:motivation)=\n",
"(surface-protein-quality-control-key-takeaway-1)=\n",
"## Motivation"
]
},
Expand Down

0 comments on commit e485832

Please sign in to comment.