Feature Request: `assay` option for `FeaturePlot`

[assaron]

Motivation

Currently, using FeaturePlot with a non-default assay is somewhat annoying, because there is no option to specify the assay.

Feature Description

Preparing the data:

library(Seurat)
library(SeuratData)
cbmc <- LoadData("cbmc")

cbmc <- NormalizeData(cbmc)
cbmc <- FindVariableFeatures(cbmc, selection.method = "vst", nfeatures = 2000, verbose = FALSE)

cbmc <- ScaleData(cbmc, features = VariableFeatures(cbmc), verbose = FALSE)
cbmc <- RunPCA(cbmc, features = VariableFeatures(cbmc), npcs = 30, verbose = FALSE)

cbmc <- RunUMAP(cbmc, dims = 1:30, reduction = "pca", verbose = FALSE)

FeaturePlot(cbmc, "CD3D")

I would expect the following code to generate a CD3 plot from ADT assay without any warnings:

FeaturePlot(cbmc, "CD3", assay="ADT")

Currently it fails:

Error in FeaturePlot(cbmc, "CD3", assay = "ADT") : 
  unused argument (assay = "ADT")

Alternatives

Current workarounds are:

# works but with a warning: Could not find CD3 in the default search locations, found in ‘ADT’ assay instead 
FeaturePlot(cbmc, "CD3") 

# works without warning but have to modify the feature name
FeaturePlot(cbmc, "adt_CD3")

I think my suggestion above is much cleaner.

[samuel-marsh]

Hi @assaron,

Not member of dev team but hopefully can be helpful. The devs can chime in to be sure but I would guess that the rationale for lack of assay parameter is due to desire to allow simultaneous plotting from multiple assays in one function call (see reprex at bottom for example). Is there a reason that the warning message functionality as current implemented is problematic?

Additionally, the proposed PR in SeuratObject seems potentially problematic as well, by making Seurat level FetchData assay specific it would prevent pulling data from multiple assays if desired and likely cause significant downstream codebase issues given ubiquity of FetchData function.

# get CD3 ADT and CD4 RNA data
adt_and_rna <- FetchData(cbmc, vars = c("CD3", "CD4"))

head(adt_and_rna)
                 adt_CD3       CD4
CTGTTTACACCGCTAG      60 0.0000000
CTCTACGGTGTGGCTC      52 0.0000000
AGCAGCCAGGCTCATT      89 0.0000000
GAATAAGAGATCCCAT      55 0.0000000
GTGCATAGTCATGCAT      63 0.0000000
TACACGACACATCCGG      82 0.4281501

As FYI FetchData can already be forced to assay specificity by specifying assay in the call:

# RNA is default assay so object level call retrieves RNA data
DefaultAssay(cbmc)
cd4_rna <- FetchData(cbmc, vars = "CD4")

head(cd4_rna)
                       CD4
CTGTTTACACCGCTAG 0.0000000
CTCTACGGTGTGGCTC 0.0000000
AGCAGCCAGGCTCATT 0.0000000
GAATAAGAGATCCCAT 0.0000000
GTGCATAGTCATGCAT 0.0000000
TACACGACACATCCGG 0.4281501

# Specify assay in the call to pull only CD4 ads data
cd4_adt <- FetchData(cbmc[["ADT"]], vars = "CD4")

head(cd4_adt)
                 CD4
CTGTTTACACCGCTAG  72
CTCTACGGTGTGGCTC  49
AGCAGCCAGGCTCATT 112
GAATAAGAGATCCCAT  66
GTGCATAGTCATGCAT  80
TACACGACACATCCGG  78

If there is something else I'm missing let me know but this would seem to create more issues than it would solve.

Best,
Sam

library(Seurat)
#> Loading required package: SeuratObject
#> Loading required package: sp
#> 
#> Attaching package: 'SeuratObject'
#> The following objects are masked from 'package:base':
#> 
#>     intersect, t
library(SeuratData)
#> ── Installed datasets ──────────────────────────────── SeuratData v0.2.2.9002 ──
#> ✔ bmcite         0.3.0                  ✔ pbmcMultiome   0.1.4
#> ✔ cbmc           3.1.4                  ✔ pbmcref        1.0.0
#> ✔ hcabm40k       3.0.0                  ✔ pbmcsca        3.0.0
#> ✔ ifnb           3.1.0                  ✔ ssHippo        3.1.4
#> ✔ mousecortexref 1.0.0                  ✔ stxBrain       0.1.2
#> ✔ pbmc3k         3.1.4                  ✔ stxKidney      0.1.0
#> ────────────────────────────────────── Key ─────────────────────────────────────
#> ✔ Dataset loaded successfully
#> ❯ Dataset built with a newer version of Seurat than installed
#> ❓ Unknown version of Seurat installed

cbmc <- LoadData("cbmc")
#> Validating object structure
#> Updating object slots
#> Ensuring keys are in the proper structure
#> Warning: Assay RNA changing from Assay to Assay
#> Warning: Assay ADT changing from Assay to Assay
#> Ensuring keys are in the proper structure
#> Ensuring feature names don't have underscores or pipes
#> Updating slots in RNA
#> Updating slots in ADT
#> Validating object structure for Assay 'RNA'
#> Validating object structure for Assay 'ADT'
#> Object representation is consistent with the most current Seurat version
#> Warning: Assay RNA changing from Assay to Assay5
#> Warning: Assay ADT changing from Assay to Assay5

cbmc <- NormalizeData(cbmc)
#> Normalizing layer: counts
cbmc <- FindVariableFeatures(cbmc, selection.method = "vst", nfeatures = 2000, verbose = FALSE)

cbmc <- ScaleData(cbmc, features = VariableFeatures(cbmc), verbose = FALSE)
cbmc <- RunPCA(cbmc, features = VariableFeatures(cbmc), npcs = 10, verbose = FALSE)

cbmc <- RunUMAP(cbmc, dims = 1:10, reduction = "pca", verbose = FALSE)
#> Warning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
#> To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
#> This message will be shown once per session

FeaturePlot(cbmc, c("CD3", "CD3E"))
#> Warning: Could not find CD3 in the default search locations, found in 'ADT'
#> assay instead

^{Created on 2026-01-08 with reprex v2.1.1}

Session info

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[assaron]

Hi @samuel-marsh,

Thanks for your comments. I think I should need to clarify a couple of things.

What I propose, is to have the code FeaturePlot(cbmc, "CD3", assay="ADT") to be equivalent to:

old.assay <- DefaultAssay(cbmc)
DefaultAssay(cbmc) <- "ADT"
FeaturePlot(cbmc, "CD3")
DefaultAssay(cbmc) <- old.assay

Meaning that, it should not limit, where the features are coming from, but change what is the primary assay for feature search. This is the type of behavior that was introduced by the FetchData PR. So your suggested potential problem for both FeaturePlot and FetchData should not be a problem, with the old code continuing to work perfectly fine (the only thing that I see as potential problematic is that someone might use ordered unnamed arguments, but which I assume is non-existent, but anyway can be fixed by moving assay to the end of the arguments).

Is there a reason that the warning message functionality as current implemented is problematic?

We are considering to introduce this kind of usage as a recommended workflow of working with cell-level gene set scores in our fgsea package, and I'm reluctant to have a recommended workflow with warnings. Moreover, I forgot to mention it in the original post, it renames the feature to have the assay key prefix (adt_ in the example), which is also not very continent. Constantly changing the default assay is also annoying.

While it's not a show-stopper, but I think it would make the usage of Seurat a bit better without any downsides: the proposed behavior is backward-compatible, doesn't introduce any complex logic, and relatively straightforward to implement (it basically a one-line change in the Seurat package over the FetchData PR).

[ollieeknight]

hi @assaron, the easy fix here is to add modify your code to simply be FeaturePlot(cbmc, c("adt_CD3", 'rna_CD3E)). a more intiutive example is FeaturePlot(cbmc, c("adt_CD4", 'rna_CD4)) as here the protein and gene names are the same. I find this to be a good way for presentations because it avoids people asking "what modality is that?"

[assaron]

@ollieeknight thanks, but I'm not looking for a workaround here. I don't want to have an assay prefix in the plot, since I'm interested in plotting gene set scores (e.g., HALLMARK_HYPOXIA), which are quite different from gene names, so the additional prefix just takes up space for nothing. And, as I said, this feature is very easy to implement (which I'm ready to finish) and doesn't seem to have any drawbacks.