106 lines
3.7 KiB
Markdown
106 lines
3.7 KiB
Markdown
# FastCAR
|
|
|
|
FastCAR is an R package to remove ambient RNA from cells in droplet based single cell RNA sequencing data.
|
|
|
|
|
|
### Installation
|
|
|
|
FastCAR can be installed from git with the following command.
|
|
|
|
```
|
|
devtools::install_git("https://git.web.rug.nl/P278949/FastCAR")
|
|
```
|
|
|
|
Running FastCAR is quite simple.
|
|
First load the library and dependencies.
|
|
|
|
```
|
|
library(Matrix)
|
|
library(Seurat)
|
|
library(qlcMatrix)
|
|
library(FastCAR)
|
|
```
|
|
Specify the locations of the expression matrices
|
|
|
|
```
|
|
cellExpressionFolder = c("Cellranger_output/sample1/filtered_feature_bc_matrix/")
|
|
fullMatrixFolder = c("Cellranger_output/sample1/raw_feature_bc_matrix/")
|
|
```
|
|
Load both the cell matrix and the full matrix
|
|
```
|
|
cellMatrix = read.cell.matrix(cellExpressionFolder)
|
|
fullMatrix = read.full.matrix(fullMatrixFolder)
|
|
```
|
|
The following functions give an idea of the effect that different settings have on the ambient RNA profile.
|
|
These are optional as they do take a few minutes and the default settings work fine
|
|
Plotting the number of empty droplets, the number of genes identified in the ambient RNA, and the number of genes that will be corrected for at different UMI cutoffs,
|
|
|
|
```
|
|
ambProfile = describe.ambient.RNA.sequence(fullCellMatrix = fullMatrix,
|
|
start = 10,
|
|
stop = 500,
|
|
by = 10,
|
|
contaminationChanceCutoff = 0.05)
|
|
|
|
plot.ambient.profile(ambProfile)
|
|
```
|
|
|
|
|
|
|
|
Set the empty droplet cutoff and the contamination chance cutoff
|
|
|
|
The empty droplet cutoff is the number of UMIs a droplet can contain at the most to be considered empty.
|
|
100 works fine but we tested this method in only one tissue. For other tissues these settings may need to be changed.
|
|
Increasing this number also increases the highest possible value of expression of a given gene.
|
|
As the correction will remove this value from every cell it is adviced not to set this too high and thereby overcorrect the expression in lowly expressing cells.
|
|
|
|
The contamination chance cutoff is the allowed probability of a gene contaminating a cell.
|
|
As we developed FastCAR specifically for differential expression analyses between groups we suggest setting this such that not enough cells could be contaminated to affect this.
|
|
In a cluster of a thousand cells divided into two groups there would be 2-3 cells per group with ambient RNA contamination of any given gene.
|
|
Such low cell numbers are disregarded for differential expression analyses.
|
|
|
|
There is an experimental function that gives a recommendation based on the ambient profiling results.
|
|
This selects the first instance of the maximum number of genes being corrected for.
|
|
I have no idea yet if this is actually a good idea.
|
|
|
|
```
|
|
emptyDropletCutoff = recommend.empty.cutoff(ambProfile)
|
|
```
|
|
|
|
|
|
```
|
|
emptyDropletCutoff = 100
|
|
contaminationChanceCutoff = 0.05
|
|
```
|
|
|
|
Determine the ambient RNA profile and remove the ambient RNA from each cell
|
|
```
|
|
ambientProfile = determine.background.to.remove(fullMatrix, cellMatrix, emptyDropletCutoff, contaminationChanceCutoff)
|
|
cellMatrix = remove.background(cellMatrix, ambientProfile)
|
|
```
|
|
|
|
This corrected matrix can be used to to make a Seurat object
|
|
|
|
```
|
|
seuratObject = CreateSeuratObject(cellMatrix)
|
|
```
|
|
|
|
|
|
## Authors
|
|
|
|
* **Marijn Berg** - m.berg@umcg.nl
|
|
|
|
## License
|
|
|
|
This project is licensed under the GPL-3 License - see the [LICENSE.md](LICENSE.md) file for details
|
|
|
|
## Changelog
|
|
|
|
### v0.1
|
|
First fully working version of the R package
|
|
|
|
### v0.2
|
|
Fixed function to write the corrected matrix to file.
|
|
Added readout of which genes will be corrected for and how many reads will be removed per cell
|
|
Added some input checks to functions
|