Featureplot not plotting if one of the variables is missing from the seurat object

[Prathyusha-konda]

Feature plot quits plotting if one of the variables is missing instead of plotting existing variables.

Error in FetchData.Seurat(object = seurat_object, vars = features[i], :
None of the requested variables were found: CD279

sessionInfo()
R version 4.2.1 (2022-06-23)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 16.04.7 LTS

Matrix products: default
BLAS: /usr/lib/atlas-base/atlas/libblas.so.3.0
LAPACK: /opt/R/4.2.1/lib/R/lib/libRlapack.so

locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C

attached base packages:
[1] stats graphics grDevices utils datasets methods base

other attached packages:
[1] readr_2.1.3 scCustomize_0.7.0 RColorBrewer_1.1-3 glmGamPoi_1.9.2 pheatmap_1.0.12 cowplot_1.1.1
[7] patchwork_1.1.2 sp_1.5-0 SeuratObject_4.1.2 Seurat_4.2.0 dplyr_1.0.10

[samuel-marsh]

Hi,

Could you please post the full code that you are running which causes the error? Also, if you update scCustomize to the develop branch does that resolve the issue?

devtools::install_github(repo = "samuel-marsh/scCustomize", ref = "develop")

When I run the following code (using dev branch) it seems to work ok.

library(tidyverse)
library(scCustomize)
library(Seurat)

pbmc <- pbmc3k.SeuratData::pbmc3k.final
pbmc <- UpdateSeuratObject(pbmc)

FeaturePlot_scCustom(seurat_object = pbmc, c("FOS", "fdskjf", "CD3E"))

Warning message:
In FetchData.Seurat(object = object, vars = c(dims, "ident", features),  :
  The following requested variables were not found: fdskjf

Best,
Sam

[Prathyusha-konda]

Hi Sam @samuel-marsh , thanks for the quick response. So it looks like featureplot doesn't plot when you include 'split.by' option and have a missing variable in the list. Without split.by, it works fine even with missing variable. This error also applies to Iterate_FeaturePlot_scCustom

Example code to reproduce using seurat's ifnb data

install dataset

InstallData("ifnb")

load dataset

LoadData("ifnb")

split the dataset into a list of two seurat objects (stim and CTRL)

ifnb.list <- SplitObject(ifnb, split.by = "stim")

ctrl <- ifnb.list[["CTRL"]]
stim <- ifnb.list[["STIM"]]

normalize and run dimensionality reduction on control dataset

ctrl <- SCTransform(ctrl, vst.flavor = "v2", verbose = FALSE) %>%
RunPCA(npcs = 30, verbose = FALSE)

stim <- SCTransform(stim, vst.flavor = "v2", verbose = FALSE) %>%
RunPCA(npcs = 30, verbose = FALSE)

ifnb.list <- list(ctrl = ctrl, stim = stim)
features <- SelectIntegrationFeatures(object.list = ifnb.list, nfeatures = 3000)
ifnb.list <- PrepSCTIntegration(object.list = ifnb.list, anchor.features = features)

immune.anchors <- FindIntegrationAnchors(object.list = ifnb.list, normalization.method = "SCT",
anchor.features = features)
immune.combined.sct <- IntegrateData(anchorset = immune.anchors, normalization.method = "SCT")

immune.combined.sct <- RunPCA(immune.combined.sct, verbose = FALSE)
immune.combined.sct <- RunUMAP(immune.combined.sct, reduction = "pca", dims = 1:30, verbose = FALSE)
immune.combined.sct <- FindNeighbors(immune.combined.sct, reduction = "pca", dims = 1:30)
immune.combined.sct <- FindClusters(immune.combined.sct, resolution = 0.3)

immune.combined.sct$celltype.stim <- paste(immune.combined.sct$seurat_annotations, immune.combined.sct$stim,
sep = "_")
Idents(immune.combined.sct) <- "celltype.stim"

pdf("featureplot_test.pdf")
FeaturePlot_scCustom(immune.combined.sct, features = c("CD3D", "GNLY", "FLT1"),split.by="stim")
dev.off()

Found the following features in more than one assay, excluding the default. We will not include these in the final data frame: FLT1Error in FetchData.Seurat(object = seurat_object, vars = features[i], :
None of the requested variables were found: FLT1

[samuel-marsh]

Gotcha, thanks! Now I understand why that's happening. I will work on patch for release this week.

In mean time you can run:

gene_plot <- c(...)

found_features <- Gene_Present(data = obj, gene_list =  genes_plot)[[1]]

That will return a vector of genes found within the object.

I will try and get patch out in next day or two (with release of scCustomize v1.0.0).

Thanks!
Sam

[samuel-marsh]

Ok fix is live in the develop branch v(0.7.0.9951).

If setting split.by the function will check for features against the assay features and meta data columns and return a warning of which features were not found and return plot with found features.

If you have any issues once updated please let me know and I'll reopen the issue.

Best,
Sam

[Prathyusha-konda]

Ok fix is live in the develop branch v(0.7.0.9951).

If setting split.by the function will check for features against the assay features and meta data columns and return a warning of which features were not found and return plot with found features.

If you have any issues once updated please let me know and I'll reopen the issue.

Best, Sam

That's awesome! Thank you, Sam! Looking forward to the new release 👍 💯

[samuel-marsh]

glad to help!!! :)