2
$\begingroup$

I want to identify MDSCs cells which don't not express HLA-DRs (HLA-DR negative) but express CD14, CD33, and ITGAM

For this, I firstly plotted a feature plot to locate HLA-DR by

cd.features <- list(grep(pattern = '^HLA-DR', x = rownames(x = pbmc_small), value = TRUE))

pbmc_small <- AddModuleScore(object = pbmc_small, features = cd.features, ctrl = 5, name = 'CDFeatures')


FeaturePlot(object = pbmc_small, features = 'CDFeatures1')& 
+     scale_colour_gradientn(colours = rev(brewer.pal(n = 11, name = "RdBu")))

Which returned

enter image description here

For CD14, CD33, and ITGAM I done

> cd.features=list(c("CD14", "CD33",  "ITGAM"))
> pbmc_small <- AddModuleScore(object = pbmc_small, features = cd.features, ctrl = 5, name = 'CDFeatures')
> FeaturePlot(object = pbmc_small, features = 'CDFeatures1')& 
+     scale_colour_gradientn(colours = rev(brewer.pal(n = 11, name = "RdBu")))

> 

Which returned

enter image description here

By looking at these two plots I really can not say which part of plot is HLA-DR negative but expressing CD14, CD33, and ITGAM

Do you know a way to do this?

Plotting options don't help because looking at the below plots you can not say which cells are HLA negative and CD14 positive

enter image description here

enter image description here

$\endgroup$
4
  • $\begingroup$ Will the user who flagged for this post to be closed please add a comment stating why they think this post should be closed? I don't see any problem with it. $\endgroup$
    – Ram RS
    Feb 16, 2022 at 20:07
  • $\begingroup$ My small comment, I'd simply use ggplot2 if I was using R (not hugely helpful). It is a lot more powerful though. @RamRS point: It is a very clear question, nicely presented on a good subject. I can make a good educated guess why someone did this, but its really for meta. Closing questions is a current topic there. It is unlikely the question will be closed - its just a vote. (For the record I upvoted.) $\endgroup$
    – M__
    Feb 17, 2022 at 3:40
  • $\begingroup$ @haci will know this, but will have to get into cellular immunology. $\endgroup$
    – M__
    Feb 17, 2022 at 3:40
  • $\begingroup$ Thinking about it you really want a third axis and a good viewing angle. Plotly might be a better option than featurePlot. Interesting but not my thing. $\endgroup$
    – M__
    Feb 17, 2022 at 3:47

2 Answers 2

2
$\begingroup$

Very old question, but recently modified, which means that someone might still be looking into this.

I usually prefer to use Ucell as the signatures are calculated within cells, which makes comparisons a bit easier. In addition is allows the formulation of signatures with both positive and negative genes.

hladr_genes <- grep(pattern = '^HLA-DR', x = rownames(x = pbmc_small), value = TRUE)
signatures_list <- list(MDSCs = c("CD14+","CD33+","ITGAM+",paste0(hladr_genes,"-")))

> signatures_list
$MDSCs
[1] "CD14+"     "CD33+"     "ITGAM+"    "HLA-DRA-"  "HLA-DRB5-" "HLA-DRB1-"

# calculate signature
pbmc_small <- AddModuleScore_UCell(pbmc_small,signatures_list,ncores = 8,name = "")
# perform smoothing
pbmc_small <- SmoothKNN(pbmc_small, signature.names = names(signatures_list), reduction="pca")
$\endgroup$
1
$\begingroup$

You need to make a transformed variable to the gene sets of interest. I would rescale the data on a range of 0-1. Then you can make a log2 ratio of the sum(set1)/sum(set2). You could explore other transformations, but this will give contrasting values for high set1 and high set2, but neutral if the expression is similar between the sets.

$\endgroup$
1
  • $\begingroup$ Your answer could be improved with additional supporting information. Please edit to add further details, such as citations or documentation, so that others can confirm that your answer is correct. You can find more information on how to write good answers in the help center. $\endgroup$
    – Community Bot
    Mar 15, 2023 at 15:09

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.

Not the answer you're looking for? Browse other questions tagged or ask your own question.