Hello! I ran SCTransform from Seurat on only cancer cells from a few patients (individually) and some cells are showing very low gene expression for all genes. When running FindAllMarkers the clusters with these cells are vastly defined by negative markers: Top 10 Genes returned for cluster in question (light blue bottom right):

I also noted the pattern of expression matches with nCount_SCT (3rd row, 3rd from left) and this is true of my other samples.

After extracting a column from the counts matrix of of SCT and RNA for a single cell from each end of the UMAP, I saw SCTransform resulted in counts dropping for that cell (Row 2-3, histogram of expression across all genes for one cell pre and post transformation, row 4-5 show expression for each gene pre and post transformation):

Is there anything I can do about this? Why is this happening?

Thank you for your help!

My Session:

R version 4.3.2 (2023-10-31)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 22.04.3 LTS

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3 
LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.so;  LAPACK version 3.10.0

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

time zone: Etc/UTC
tzcode source: system (glibc)

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

other attached packages:
 [1] lubridate_1.9.3       forcats_1.0.0         purrr_1.0.2           readr_2.1.5           tidyr_1.3.1           tibble_3.2.1          tidyverse_2.0.0      
 [8] qs_0.25.7             stringr_1.5.1         openxlsx_4.2.5.2      dplyr_1.1.4           data.table_1.15.2     RColorBrewer_1.1-3    patchwork_1.2.0      
[15] ggplot2_3.5.0         SeuratDisk_0.0.0.9021 Seurat_5.0.1          SeuratObject_5.0.1    sp_2.1-3             

loaded via a namespace (and not attached):
  [1] RcppAnnoy_0.0.22              splines_4.3.2                 later_1.3.2                   bitops_1.0-7                  filelock_1.0.3               
  [6] polyclip_1.10-6               fastDummies_1.7.3             lifecycle_1.0.4               hdf5r_1.3.10                  globals_0.16.3               
 [11] lattice_0.22-5                MASS_7.3-60                   magrittr_2.0.3                rmarkdown_2.26                plotly_4.10.4                
 [16] yaml_2.3.8                    httpuv_1.6.14                 sctransform_0.4.1             zip_2.3.1                     spam_2.10-0                  
 [21] spatstat.sparse_3.0-3         reticulate_1.35.0             cowplot_1.1.3                 pbapply_1.7-2                 DBI_1.2.2                    
 [26] abind_1.4-5                   zlibbioc_1.48.2               Rtsne_0.17                    GenomicRanges_1.54.1          BiocGenerics_0.48.1          
 [31] RCurl_1.98-1.14               rappdirs_0.3.3                GenomeInfoDbData_1.2.11       IRanges_2.36.0                S4Vectors_0.40.2             
 [36] ggrepel_0.9.5                 irlba_2.3.5.1                 listenv_0.9.1                 spatstat.utils_3.0-4          goftest_1.2-3                
 [41] RSpectra_0.16-1               spatstat.random_3.2-3         fitdistrplus_1.1-11           parallelly_1.37.1             leiden_0.4.3.1               
 [46] codetools_0.2-19              DelayedArray_0.28.0           RApiSerialize_0.1.2           tidyselect_1.2.1              farver_2.1.1                 
 [51] UCell_2.6.2                   matrixStats_1.2.0             stats4_4.3.2                  BiocFileCache_2.10.1          spatstat.explore_3.2-6       
 [56] jsonlite_1.8.8                BiocNeighbors_1.20.2          ellipsis_0.3.2                progressr_0.14.0              ggridges_0.5.6               
 [61] survival_3.5-7                tools_4.3.2                   ica_1.0-3                     Rcpp_1.0.12                   glue_1.7.0                   
 [66] gridExtra_2.3                 SparseArray_1.2.4             xfun_0.42                     MatrixGenerics_1.14.0         GenomeInfoDb_1.38.7          
 [71] withr_3.0.0                   BiocManager_1.30.22           fastmap_1.1.1                 fansi_1.0.6                   digest_0.6.35                
 [76] timechange_0.3.0              R6_2.5.1                      mime_0.12                     colorspace_2.1-0              scattermore_1.2              
 [81] tensor_1.5                    spatstat.data_3.0-4           RSQLite_2.3.5                 utf8_1.2.4                    generics_0.1.3               
 [86] httr_1.4.7                    htmlwidgets_1.6.4             S4Arrays_1.2.1                uwot_0.1.16                   pkgconfig_2.0.3              
 [91] gtable_0.3.4                  blob_1.2.4                    lmtest_0.9-40                 SingleCellExperiment_1.24.0   XVector_0.42.0               
 [96] htmltools_0.5.7               dotCall64_1.1-1               scales_1.3.0                  Biobase_2.62.0                png_0.1-8                    
[101] knitr_1.45                    rstudioapi_0.15.0             tzdb_0.4.0                    reshape2_1.4.4                nlme_3.1-163                 
[106] curl_5.2.1                    cachem_1.0.8                  zoo_1.8-12                    BiocVersion_3.18.1            KernSmooth_2.23-22           
[111] parallel_4.3.2                miniUI_0.1.1.1                AnnotationDbi_1.64.1          pillar_1.9.0                  grid_4.3.2                   
[116] vctrs_0.6.5                   RANN_2.6.1                    promises_1.2.1                stringfish_0.16.0             dbplyr_2.4.0                 
[121] xtable_1.8-4                  cluster_2.1.4                 evaluate_0.23                 cli_3.6.2                     compiler_4.3.2               
[126] rlang_1.1.3                   crayon_1.5.2                  future.apply_1.11.1           labeling_0.4.3                plyr_1.8.9                   
[131] stringi_1.8.3                 viridisLite_0.4.2             deldir_2.0-4                  BiocParallel_1.36.0           munsell_0.5.0                
[136] Biostrings_2.70.3             lazyeval_0.2.2                spatstat.geom_3.2-9           Matrix_1.6-5                  ExperimentHub_2.10.0         
[141] RcppHNSW_0.6.0                hms_1.1.3                     bit64_4.0.5                   future_1.33.1                 KEGGREST_1.42.0              
[146] shiny_1.8.0                   SummarizedExperiment_1.32.0   interactiveDisplayBase_1.40.0 AnnotationHub_3.10.0          ROCR_1.0-11                  
[151] igraph_2.0.3                  memoise_2.0.1                 RcppParallel_5.1.7            bit_4.0.5