FeaturePlot() in Seurat v5 object #9951
-
|
Hello, I integrated 3 Seurat objects together, and now in my "RNA" assay, I have "data.1", "data.2", "data.3", and "counts.1", "counts.2", "counts.3". If I set my default assay to be "RNA", and run FeaturePlot() on the integrated object, which layer will it use? I thought it would use assay = "RNA", layer = "data", but now there are 3 different "data" layers. I would really appreciate any help. Thank you! |
Beta Was this translation helpful? Give feedback.
Answered by
samuel-marsh
Jun 17, 2025
Replies: 1 comment 1 reply
-
|
Have you tried JoinLayers? |
Beta Was this translation helpful? Give feedback.
1 reply
-
|
Best, library(Seurat)
#> Loading required package: SeuratObject
#> Loading required package: sp
#>
#> Attaching package: 'SeuratObject'
#> The following objects are masked from 'package:base':
#>
#> intersect, t
library(scCustomize)
#> scCustomize v3.0.1.34
#> If you find the scCustomize useful please cite.
#> See 'samuel-marsh.github.io/scCustomize/articles/FAQ.html' for citation info.
pbmc <- pbmc3k.SeuratData::pbmc3k.final
pbmc <- UpdateSeuratObject(pbmc)
#> Validating object structure
#> Updating object slots
#> Ensuring keys are in the proper structure
#> Updating matrix keys for DimReduc 'pca'
#> Updating matrix keys for DimReduc 'umap'
#> Warning: Assay RNA changing from Assay to Assay
#> Warning: Graph RNA_nn changing from Graph to Graph
#> Warning: Graph RNA_snn changing from Graph to Graph
#> Warning: DimReduc pca changing from DimReduc to DimReduc
#> Warning: DimReduc umap changing from DimReduc to DimReduc
#> Ensuring keys are in the proper structure
#> Ensuring feature names don't have underscores or pipes
#> Updating slots in RNA
#> Updating slots in RNA_nn
#> Setting default assay of RNA_nn to RNA
#> Updating slots in RNA_snn
#> Setting default assay of RNA_snn to RNA
#> Updating slots in pca
#> Updating slots in umap
#> Setting umap DimReduc to global
#> Setting assay used for NormalizeData.RNA to RNA
#> Setting assay used for FindVariableFeatures.RNA to RNA
#> Setting assay used for ScaleData.RNA to RNA
#> Setting assay used for RunPCA.RNA to RNA
#> Setting assay used for JackStraw.RNA.pca to RNA
#> No assay information could be found for ScoreJackStraw
#> Warning: Adding a command log without an assay associated with it
#> Setting assay used for FindNeighbors.RNA.pca to RNA
#> No assay information could be found for FindClusters
#> Warning: Adding a command log without an assay associated with it
#> Setting assay used for RunUMAP.RNA.pca to RNA
#> Validating object structure for Assay 'RNA'
#> Validating object structure for Graph 'RNA_nn'
#> Validating object structure for Graph 'RNA_snn'
#> Validating object structure for DimReduc 'pca'
#> Validating object structure for DimReduc 'umap'
#> Object representation is consistent with the most current Seurat version
pbmc$sample_id <- sample(c("sample1", "sample2", "sample3", "sample4", "sample5", "sample6"), size = ncol(pbmc),
replace = TRUE)
pbmc <- Split_Layers(seurat_object = pbmc, split.by = "sample_id")
#> • Splitting layers within assay: RNA into 6 parts by "sample_id"
#> ℹ RNA is not Assay5, converting to Assay5 before splitting.
#> Splitting 'counts', 'data' layers. Not splitting 'scale.data'. If you would like to split other layers, set in `layers` argument.
nrow(FetchData(object = pbmc, vars = "ACTB"))
#> [1] 2638
length(Cells(pbmc))
#> [1] 2638Created on 2025-06-17 with reprex v2.1.1
|
Beta Was this translation helpful? Give feedback.
Answer selected by
samuel-marsh
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
JoinLayersis not needed for plotting functions. Internally, they automatically collect data from all layers usingFetchData. So any layers matching pattern (i.e. data.1, data.2) will be included. Below is quick validation example showing thatFetchDatareturns data for all cells in the object regardless of it being split.Best,
Sam