https://github.com/samuel-marsh/hammond-et-al_2019_microglia_scrnaseq
Repository for "pseudo"-objects based on analysis in Hammond et al., 2019 (https://doi.org/10.1016/j.immuni.2018.11.004)
https://github.com/samuel-marsh/hammond-et-al_2019_microglia_scrnaseq
Last synced: 3 months ago
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Repository for "pseudo"-objects based on analysis in Hammond et al., 2019 (https://doi.org/10.1016/j.immuni.2018.11.004)
- Host: GitHub
- URL: https://github.com/samuel-marsh/hammond-et-al_2019_microglia_scrnaseq
- Owner: samuel-marsh
- Created: 2022-09-23T18:10:22.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2022-09-27T15:12:24.000Z (over 2 years ago)
- Last Synced: 2025-01-31T15:40:21.145Z (5 months ago)
- Language: R
- Homepage:
- Size: 3.19 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Hammond-et-al_2019_Microglia_scRNAseq
#### Analysis Objects to Download for:
### [**Single-Cell RNA Sequencing of Microglia throughout the Mouse Lifespan and in the Injured Brain Reveals Complex Cell-State Changes (*Immunity*)**](https://doi.org/10.1016/j.immuni.2018.11.004)
**Timothy R. Hammond1,\***, Connor Dufort, Lasse Dissing-Olesen, Stefanie Giera, Adam Young, Alec Wysoker, Alec J. Walker, Frederick Gergits, Michael Segel, James Nemesh, **Samuel E. Marsh2,\#**, Arpiar Saunders, Evan Macosko, Florent Ginhoux, Jinmiao Chen, Robin J.M. Franklin, Xianhua Piao, Steven A. McCarroll, and Beth Stevens.
1Performed analysis
2Created Objects/Repo
\*Analysis Contact (contact: [email protected])
\#Repo/Object Contact (contact: [email protected])
## Table of Contents
**[About the Datasets](https://github.com/samuel-marsh/Hammond-et-al_2019_Microglia_scRNAseq#about-the-datasets)**
**[Object Creation](https://github.com/samuel-marsh/Hammond-et-al_2019_Microglia_scRNAseq#object-creation)**
**[Downloading Objects](https://github.com/samuel-marsh/Hammond-et-al_2019_Microglia_scRNAseq#downloading-objects)**
**[Loading & Basic Use of Objects](https://github.com/samuel-marsh/Hammond-et-al_2019_Microglia_scRNAseq#using-objects)**
## About the Datasets
Analysis was performed in paper as described without use of bespoke object/file format. However, to facilitate easier use of data in analyzed/annotated form we have created pseudo-objects.
*NOTE: If you would like to query individual genes and their expression across clusters/ages you can use interactive web portal [microgliasinglecell.com](https://microgliasinglecell.com).*
Objects described in this repo are available in 3 most popular formats for use in both R and Python (Seurat, SingleCellExperiment, and anndata).
*The objects contain:*
- Raw & Normalized expression data.
- tSNE coordinates of analysis shown in paper.
- Cluster annotation from paper.
- Cell level meta data (age, sex, batch, etc)
*They do not contain:*
- Variable genes
- ICA factor loadings
- Scaled Data (removed to keep object size small, can be added using package functions)
### Object Creation
#### Downloading data
Raw data matrices can be downloaded using browser from NCBI GEO [GSE121654](https://www.ncbi.nlm.nih.gov/geo/download/?acc=GSE121654&format=file). If using command line you can use [ffq tool from Pacther lab](https://github.com/pachterlab/ffq).
#### Creating Objects
Raw data matrices were then processed in R using [scCustomize](https://samuel-marsh.github.io/scCustomize/) & [Seurat](https://github.com/satijalab/seurat) to create Seurat objects. The steps and functions used for object creation are detailed in script: [01_Object_Creation.R](https://github.com/samuel-marsh/Hammond-et-al_2019_Microglia_scRNAseq/blob/main/01_Object_Creation.R).
Objects were then converted (see [02_Object_Conversion.R](https://github.com/samuel-marsh/Hammond-et-al_2019_Microglia_scRNAseq/blob/main/02_Object_Conversion.R)) to SingleCellExperiment using `Seurat::as.SingleCellExperiment()` and anndata using `sceasy::convertFormat` functions.
## Downloading Objects
Dataset objects can be downloaded from figshare either using browser or command line as detailed below.
### Download via browser
Datasets can be downloaded through browser using the following links:
| Dataset | Figures | Type | Link |
| :-----: | :-----: | :------: | :------------: |
| All Samples | Figure 1 | [Seurat](https://github.com/satijalab/seurat/wiki/Seurat) | [All Sample Seurat](https://figshare.com/ndownloader/files/37624052) |
| All Samples | Figure 1 | [SCE](https://bioconductor.org/packages/release/bioc/html/SingleCellExperiment.html) | [All Sample SCE](https://figshare.com/ndownloader/files/37624058) |
| All Samples | Figure 1 | [anndata](https://anndata.readthedocs.io/en/latest/) | [All Sample anndata](https://figshare.com/ndownloader/files/37624073) |
| Young vs. Old | Figure 5 | [Seurat](https://github.com/satijalab/seurat/wiki/Seurat) | [Young vs. Old Seurat](https://figshare.com/ndownloader/files/37606217) |
| Young vs. Old | Figure 5 | [SCE](https://bioconductor.org/packages/release/bioc/html/SingleCellExperiment.html) | [Young vs. Old SCE](https://figshare.com/ndownloader/files/37606379) |
| Young vs. Old | Figure 5 | [anndata](https://anndata.readthedocs.io/en/latest/) | [Young vs. Old anndata](https://figshare.com/ndownloader/files/37610789) |
### Download via command line
**Seurat Objects**
```
# Download both objects in .zip
wget -O hammond_seurat.zip https://figshare.com/ndownloader/articles/21201463/versions/4
# Download All Samples Object
wget -O Hammond_et-al-2019_Seurat_Converted_v4.qs https://figshare.com/ndownloader/files/37624052
# Download Young vs. Old Samples Object
wget -O Hammond_et-al-2019_Aged_Seurat_Converted_v4.qs https://figshare.com/ndownloader/files/37606217
```
**SCE Objects**
```
# Download both objects in .zip
wget -O hammond_SCE.zip https://figshare.com/ndownloader/articles/21201472/versions/3
# Download All Samples Object
wget -O Hammond_et-al-2019_SCE_Converted_v1-16-0.qs https://figshare.com/ndownloader/files/37624058
# Download Young vs. Old Samples Object
wget -O Hammond_et-al-2019_Aged_SCE_Converted_v1-16-0.qs https://figshare.com/ndownloader/files/37606379
```
**anndata Objects**
```
# Download both objects in .zip
wget -O hammond_anndata.zip https://figshare.com/ndownloader/articles/21201616/versions/5
# Download All Samples Object
wget -O Hammond_et-al-2019_anndata_Converted_v0-8-0.h5ad https://figshare.com/ndownloader/files/37624073
# Download Young vs. Old Samples Object
wget -O Hammond_et-al-2019_Aged_anndata_Converted_v0-8-0.h5ad https://figshare.com/ndownloader/files/37610789
```
## Using Objects
### Using Objects in R
Examples of some basic use and plotting of Seurat and SCE objects can be found in script: [03_Object_Usage_R.R](https://github.com/samuel-marsh/Hammond-et-al_2019_Microglia_scRNAseq/blob/main/03_Object_Usage_R.R).
Use of Seurat object also takes advantage of the ability to use [scCustomize](https://samuel-marsh.github.io/scCustomize/) for plotting:
```
library(tidyverse)
library(Seurat) #v4.1.0
library(scCustomize) #v0.7.0.9038
library(patchwork)
p1 <- DimPlot(hammond_all_samples, cols = hammond_all_samples@misc$hammond_colors, pt.size = 0.25, raster = F, label = T, label.size = 5) + NoLegend() + ggtitle("Hammond et. al., 2019 All Samples") + theme(plot.title = element_text(hjust = 0.5))
p2 <- Cluster_Highlight_Plot(seurat_object = hammond_all_samples, cluster_name = 4, highlight_color = hammond_all_samples@misc$hammond_colors[[6]]) + ggtitle("Cluster 9") + theme(plot.title = element_text(hjust = 0.5))
p3 <- FeaturePlot_scCustom(seurat_object = hammond_all_samples, features = "Spp1")
p1 + p2 + p3
```
### Using Objects in Python
We also provide a jupyter notebook with basic commands for loading and plotting objects using scanpy/anndata: [04_Object_Usage_Scanpy.ipynb](https://github.com/samuel-marsh/Hammond-et-al_2019_Microglia_scRNAseq/blob/main/04_Object_Usage_Scanpy.ipynb)
### Color Palettes (Matching Paper Figures)
We also provide color palettes in easily accessible formats for use in either R or python. The script [05_Hammond_Color_Palettes.R](https://github.com/samuel-marsh/Hammond-et-al_2019_Microglia_scRNAseq/blob/main/05_Hammond_Color_Palettes.R) provides details of basic use.
- Seurat objects contain color palettes in the `@misc` slot of the objects.
- For either Seurat, SCE, or any other R-based use there is also a qs object [Hammond_et-al-2019_Color_Palettes.qs](https://github.com/samuel-marsh/Hammond-et-al_2019_Microglia_scRNAseq/blob/main/Hammond_et-al-2019_Color_Palettes.qs) in this repo which contains all color palettes for easy loading.
- For Python [05_Hammond_Color_Palettes.R](https://github.com/samuel-marsh/Hammond-et-al_2019_Microglia_scRNAseq/blob/main/05_Hammond_Color_Palettes.R) contains vectors formatted for copy and paste use in python.