P278949/FastCAR
1
1
Fork 0
Code Issues Pull Requests Releases Wiki Activity

updated readme and made the new function match the rest of the formatting

Browse Source
This commit is contained in:
Marijn 2020-04-27 15:50:48 +02:00
parent c457e087be
commit 40765c3a42
2 changed files with 17 additions and 10 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
R/FastCAR_Base.R
View File

@ -146,7 +146,7 @@ plot.ambient.profile = function(ambientProfile){
# I noticed that the number of genes removed tends to even out over time
# Test whether the point where this first happens is a good empty cutoff point
recommendedRemoval = function(ambientProfile){
recommend.empty.cutoff = function(ambientProfile){
highestNumberOfGenes = max(ambientProfile[,3])
firstOccurence = match(highestNumberOfGenes, ambientProfile[,3])
return(as.numeric(rownames(ambientProfile[firstOccurence,])))

25
README.md
View File

@ -26,11 +26,6 @@ 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/")
```
Set a location for storing the corrected cell/gene matrix
```
correctedMatrixFolder = c("Cellranger_output/sample1/corrected_feature_bc_matrix")
```
Load both the cell matrix and the full matrix
```
cellMatrix = read.cell.matrix(cellExpressionFolder)
@ -64,6 +59,15 @@ As we developed FastCAR specifically for differential expression analyses betwee
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
@ -75,12 +79,10 @@ ambientProfile = determine.background.to.remove(fullMatrix, cellMatrix, emptyDro
cellMatrix = remove.background(cellMatrix, ambientProfile)
```
Finally write the corrected cell/gene matrix to a file, this matrix can be used in Seurat the same way as any other cell/gene matrix.
This corrected matrix can be used to to make a Seurat object
```
write.corrected.matrix(cellMatrix, correctedMatrixFolder, ambientProfile)
seuratObject = CreateSeuratObject(cellMatrix)
```
@ -96,3 +98,8 @@ This project is licensed under the GPL-3 License - see the [LICENSE.md](LICENSE.
### 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