SpatialDimPlot and DimPlot colors do not match

[JamesJDollar]

I am trying to visualize the clusters on Dimplot and on SpatialDimPlot, but the colors will not match.
SpatialDimPlot reports the warning: 'Scale for 'fill' is already present. Adding another scale for 'fill',
which will replace the existing scale.' Specifying 'cols =' does not fix the issue either.

Thank you for your help!

[JamesJDollar]

Current work around is providing scale_color_brewer(palette = ) to DimPlot and scale_fill_brewer(palette = ) to SpatialPlot, but I am wondering if there is a better way.

[mojaveazure]

I'm not able to reproduce this. Can you provide the code you used along with a dataset, a subset of a dataset, or a dataset in SeuratData that reproduces this error along with the output of sessionInfo()?

[no-response]

This issue has been automatically closed because there has been no response to our request for more information from the original author. With only the information that is currently in the issue, we don't have enough information to take action. Please reach out if you have or find the answers we need so that we can investigate further.

[SebastienNin]

Hi,
I'm working on 10X visium data and I got the same problem as @JamesJDollar.

Here is my code

library(SeuratData)
library(Seurat)

InstallData("stxBrain.SeuratData")

brain <- LoadData("stxBrain.SeuratData", type = "anterior1")

plot1 <- VlnPlot(brain, features = "nCount_Spatial", pt.size = 0.1) + NoLegend()
plot2 <- SpatialFeaturePlot(brain, features = "nCount_Spatial") + theme(legend.position = "right")
wrap_plots(plot1, plot2)

brain <- SCTransform(brain, assay = "Spatial", verbose = FALSE)

brain <- RunPCA(brain, assay = "SCT", verbose = FALSE)
brain <- FindNeighbors(brain, reduction = "pca", dims = 1:30)
brain <- FindClusters(brain, verbose = FALSE)
brain <- RunUMAP(brain, reduction = "pca", dims = 1:30)

p1 <- DimPlot(brain, reduction = "umap", label = TRUE)
p2 <- SpatialDimPlot(brain, label = TRUE, label.size = 3)
p1 + p2

And I got this picture for the DimPlot + SpatialDimPlot

As you can see, the colors between the DimPlot and the SpatialDimPlot are different.
Can you help me to figure out what is the problem please?

Have a nice day,
Sebastien

Here is my sessionInfo()

> sessionInfo()
R version 3.6.1 (2019-07-05)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 16.04.7 LTS

Matrix products: default
BLAS:   /usr/lib/libblas/libblas.so.3.6.0
LAPACK: /usr/lib/lapack/liblapack.so.3.6.0

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

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

other attached packages:
 [1] stxBrain.SeuratData_0.1.1 SeuratData_0.2.1          patchwork_1.1.1           Seurat_3.2.2             
 [5] Rcpp_1.0.7                GGally_2.1.2              DT_0.18                   cowplot_1.1.1            
 [9] plotly_4.9.4.1            factoextra_1.0.7          reshape2_1.4.4            VennDiagram_1.6.20       
[13] futile.logger_1.4.3       ggplot2_3.3.5             pheatmap_1.0.12           htmltools_0.5.1.1        
[17] yaml_2.2.1                data.table_1.14.0        

loaded via a namespace (and not attached):
  [1] backports_1.2.1      plyr_1.8.6           igraph_1.2.6         lazyeval_0.2.2       splines_3.6.1        listenv_0.8.0       
  [7] usethis_2.0.1        digest_0.6.27        rsconnect_0.8.18     fansi_0.5.0          magrittr_2.0.1       memoise_2.0.0       
 [13] tensor_1.5           cluster_2.1.0        ROCR_1.0-11          remotes_2.4.0        globals_0.14.0       matrixStats_0.59.0  
 [19] R.utils_2.10.1       prettyunits_1.1.1    colorspace_2.0-2     rappdirs_0.3.3       ggrepel_0.9.1        xfun_0.24           
 [25] dplyr_1.0.7          callr_3.7.0          crayon_1.4.1         jsonlite_1.7.2       spatstat_1.64-1      spatstat.data_2.1-0 
 [31] survival_3.2-11      zoo_1.8-9            glue_1.4.2           polyclip_1.10-0      gtable_0.3.0         leiden_0.3.8        
 [37] pkgbuild_1.2.0       R.cache_0.15.0       future.apply_1.7.0   abind_1.4-5          scales_1.1.1         futile.options_1.0.1
 [43] DBI_1.1.1            miniUI_0.1.1.1       viridisLite_0.4.0    xtable_1.8-4         reticulate_1.20      bit_4.0.4           
 [49] rsvd_1.0.3           htmlwidgets_1.5.3    httr_1.4.2           RColorBrewer_1.1-2   ellipsis_0.3.2       ica_1.0-2           
 [55] pkgconfig_2.0.3      reshape_0.8.8        R.methodsS3_1.8.1    farver_2.1.0         sass_0.4.0           uwot_0.1.10         
 [61] deldir_0.2-10        utf8_1.2.1           tidyselect_1.1.1     labeling_0.4.2       rlang_0.4.11         later_1.2.0         
 [67] cachem_1.0.5         munsell_0.5.0        tools_3.6.1          cli_3.0.1            generics_0.1.0       devtools_2.4.2      
 [73] ggridges_0.5.3       evaluate_0.14        stringr_1.4.0        fastmap_1.1.0        goftest_1.2-2        rematch2_2.1.2      
 [79] processx_3.5.2       knitr_1.33           bit64_4.0.5          fs_1.5.0             fitdistrplus_1.1-5   purrr_0.3.4         
 [85] RANN_2.6.1           pbapply_1.4-3        future_1.21.0        nlme_3.1-141         mime_0.11            formatR_1.11        
 [91] R.oo_1.24.0          hdf5r_1.3.3          compiler_3.6.1       rstudioapi_0.13      curl_4.3.2           png_0.1-7           
 [97] testthat_3.0.4       spatstat.utils_2.2-0 tibble_3.1.2         bslib_0.2.5.1        stringi_1.7.3        ps_1.6.0            
[103] highr_0.9            desc_1.3.0           RSpectra_0.16-0      lattice_0.20-44      Matrix_1.3-2         styler_1.5.1        
[109] vctrs_0.3.8          pillar_1.6.1         lifecycle_1.0.0      BiocManager_1.30.16  lmtest_0.9-38        jquerylib_0.1.4     
[115] RcppAnnoy_0.0.18     irlba_2.3.3          httpuv_1.6.1         R6_2.5.0             bookdown_0.22        promises_1.2.0.1    
[121] KernSmooth_2.23-15   gridExtra_2.3        parallelly_1.27.0    sessioninfo_1.1.1    codetools_0.2-16     lambda.r_1.2.4      
[127] pkgload_1.2.1        MASS_7.3-54          assertthat_0.2.1     rprojroot_2.0.2      withr_2.4.2          sctransform_0.3.2   
[133] mgcv_1.8-28          parallel_3.6.1       rpart_4.1-15         tidyr_1.1.3          rmarkdown_2.9        Rtsne_0.15          
[139] shiny_1.6.0    ```

[SebastienNin]

If I do the following:

p1 <- DimPlot(brain, reduction = "umap", label = TRUE)
p2 <- SpatialDimPlot(brain)
p1 + p2

I got the good colors: