SystemToCell Error

[lnbooth]

Hi! I am getting "Error: No cell overlap between new meta data and Seurat object" when I try to run NICHES SystemToCell on either my own data or on the ifnb vignette data. CellToCell works fine for me when I set SystemToCell = F.

Any insights or help with sorting this out would be much appreciated! Thank you so much!

Here is my code (slightly modified from the very helpful NICHES vignette):

ifnb <- LoadData("ifnb")
table([email protected]$stim,[email protected]$seurat_annotations)
ifnb <- NormalizeData(ifnb)
# Set idents so that celltypes are in active identity slot
Idents(ifnb) <- "seurat_annotations"
# Split object into STIM and CTRL conditions, to calculate NICHES objects separately
data.list <- SplitObject(ifnb, split.by="stim")
data.list <- lapply(X = data.list, FUN = function(x) {
    x <- NormalizeData(x)
})
# Define the maximum number that can be sampled from all conditions
max.cells <- min(ncol(data.list[[1]]),ncol(data.list[[2]])) 
# Downsample to the same number of cells for each condition
for (i in 1:length(data.list)){
  Idents(data.list[[i]]) <- data.list[[i]]$stim
  data.list[[i]] <- subset(data.list[[i]],cells = WhichCells(data.list[[i]],downsample = max.cells))
  Idents(data.list[[i]]) <- data.list[[i]]$seurat_annotations
}
# Check resulting distributions and that the totals are the same
distribution <- data.frame(CTRL = table(Idents(data.list[[1]])),
                            STIM = table(Idents(data.list[[2]])))
distribution <- reshape2::melt(distribution)
ggplot(data = distribution,aes(x = STIM.Var1,y=value,fill = variable))+geom_bar(stat='identity',position='dodge')+
  theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust=1))+
  ggtitle('Number of Cells Per Condition')
scc.list <- list()
for(i in 1:length(data.list)){
  print(i)
  scc.list[[i]] <- RunNICHES(data.list[[i]],
                             LR.database="fantom5",
                             species="human",
                             assay="RNA",
                             cell_types = "seurat_annotations",
                             min.cells.per.ident=1,
                             min.cells.per.gene = 50,
                             meta.data.to.map = c('orig.ident','seurat_annotations','stim'),
                             SystemToCell = T,
                             CellToCell = T)
}
names(scc.list) <- names(data.list)

Output from the above code is:
[1] 1
Set cell types as Identity of object internally

Subsetting to populations with greater than 1 cells

Subsetting to genes expressed in greater than 50 cells

6548 distinct cells from 13 celltypes to be analyzed

Limiting ground truth to genes within dataset

Mapping against 246 ground truth signaling mechanisms

For sampling purposes, please make sure that the active Identity of the input seurat object corresponds to cell types

40962 Cell-To-Cell edges computed, sampling 169 distinct VectorTypes, out of 169 total possible
Error: No cell overlap between new meta data and Seurat object

And my session info:
R version 4.2.1 (2022-06-23)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.4 LTS

Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/atlas/libblas.so.3.10.3
LAPACK: /usr/lib/x86_64-linux-gnu/atlas/liblapack.so.3.10.3

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

attached base packages:
[1] stats4 grid stats graphics grDevices utils datasets methods base

other attached packages:
[1] ifnb.SeuratData_3.1.0 SeuratData_0.2.2.9001 pheatmap_1.0.12 DESeq2_1.36.0
[5] RColorBrewer_1.1-3 writexl_1.4.2 ggbeeswarm_0.7.2 TSCAN_1.34.0
[9] TrajectoryUtils_1.4.0 SingleCellExperiment_1.20.0 SummarizedExperiment_1.28.0 Biobase_2.58.0
[13] GenomicRanges_1.48.0 GenomeInfoDb_1.34.9 IRanges_2.30.1 S4Vectors_0.36.1
[17] BiocGenerics_0.44.0 MatrixGenerics_1.10.0 matrixStats_1.0.0 igraph_1.3.5
[21] gridExtra_2.3 dplyr_1.0.10 ggthemes_4.2.4 ComplexHeatmap_2.15.4
[25] cowplot_1.1.1 Connectome_1.0.1 NICHES_1.0.0 ggpubr_0.6.0
[29] ggplot2_3.4.4 SeuratObject_5.0.0 Seurat_4.3.0.1

loaded via a namespace (and not attached):
[1] rappdirs_0.3.3 scattermore_1.2 ragg_1.2.6 tidyr_1.3.0
[5] bit64_4.0.5 knitr_1.40 irlba_2.3.5.1 DelayedArray_0.24.0
[9] data.table_1.14.6 KEGGREST_1.36.3 RCurl_1.98-1.8 doParallel_1.0.17
[13] generics_0.1.3 callr_3.7.3 usethis_2.2.2 RSQLite_2.2.16
[17] RANN_2.6.1 combinat_0.0-8 future_1.33.0 bit_4.0.5
[21] spatstat.data_3.0-3 httpuv_1.6.6 assertthat_0.2.1 xfun_0.32
[25] evaluate_0.23 promises_1.2.1 fansi_1.0.4 caTools_1.18.2
[29] DBI_1.1.3 geneplotter_1.74.0 htmlwidgets_1.6.2 spatstat.geom_3.0-6
[33] purrr_1.0.2 ellipsis_0.3.2 backports_1.4.1 annotate_1.74.0
[37] deldir_1.0-9 vctrs_0.6.3 remotes_2.4.2.1 Cairo_1.6-1
[41] ROCR_1.0-11 abind_1.4-5 cachem_1.0.7 withr_2.5.2
[45] progressr_0.14.0 sctransform_0.3.5 prettyunits_1.2.0 mclust_6.0.0
[49] goftest_1.2-3 cluster_2.1.3 dotCall64_1.1-1 lazyeval_0.2.2
[53] crayon_1.5.2 genefilter_1.78.0 spatstat.explore_3.0-6 pkgconfig_2.0.3
[57] labeling_0.4.3 pkgload_1.3.3 nlme_3.1-157 vipor_0.4.5
[61] devtools_2.4.5 rlang_1.1.1 globals_0.16.2 lifecycle_1.0.4
[65] miniUI_0.1.1.1 invgamma_1.1 rprojroot_2.0.3 ggrastr_1.0.2
[69] polyclip_1.10-6 lmtest_0.9-40 Matrix_1.6-1.1 ashr_2.2-63
[73] carData_3.0-5 zoo_1.8-11 beeswarm_0.4.0 ggridges_0.5.4
[77] GlobalOptions_0.1.2 processx_3.8.2 png_0.1-8 viridisLite_0.4.2
[81] rjson_0.2.21 bitops_1.0-7 KernSmooth_2.23-20 spam_2.10-0
[85] Biostrings_2.64.1 blob_1.2.4 shape_1.4.6 mixsqp_0.3-48
[89] stringr_1.5.0 SQUAREM_2021.1 parallelly_1.36.0 spatstat.random_3.1-3
[93] rstatix_0.7.2 ggsignif_0.6.4 scales_1.2.1 memoise_2.0.1
[97] magrittr_2.0.3 plyr_1.8.9 ica_1.0-3 gplots_3.1.3
[101] zlibbioc_1.44.0 compiler_4.2.1 clue_0.3-65 fitdistrplus_1.1-11
[105] cli_3.6.1 urlchecker_1.0.1 XVector_0.38.0 listenv_0.9.0
[109] patchwork_1.1.3 pbapply_1.7-2 ps_1.7.5 MASS_7.3-58
[113] mgcv_1.8-40 tidyselect_1.2.0 stringi_1.7.12 textshaping_0.3.7
[117] yaml_2.3.6 locfit_1.5-9.8 ggrepel_0.9.3 tools_4.2.1
[121] future.apply_1.11.0 parallel_4.2.1 circlize_0.4.16 rstudioapi_0.15.0
[125] foreach_1.5.2 farver_2.1.1 Rtsne_0.16 digest_0.6.31
[129] shiny_1.7.5.1 Rcpp_1.0.10 car_3.1-2 broom_1.0.5
[133] later_1.3.1 RcppAnnoy_0.0.21 httr_1.4.7 AnnotationDbi_1.58.0
[137] colorspace_2.1-0 XML_3.99-0.14 fs_1.6.3 tensor_1.5
[141] reticulate_1.28 truncnorm_1.0-9 splines_4.2.1 uwot_0.1.14
[145] spatstat.utils_3.0-2 sp_2.1-0 sessioninfo_1.2.2 plotly_4.10.3
[149] systemfonts_1.0.5 xtable_1.8-4 jsonlite_1.8.2 R6_2.5.1
[153] profvis_0.3.8 pillar_1.9.0 htmltools_0.5.4 mime_0.12
[157] glue_1.6.2 fastmap_1.1.1 BiocParallel_1.32.5 codetools_0.2-18
[161] pkgbuild_1.4.2 utf8_1.2.3 lattice_0.20-45 spatstat.sparse_3.0-1
[165] tibble_3.2.0 curl_5.0.2 leiden_0.4.3 gtools_3.9.4
[169] survival_3.5-7 limma_3.54.2 rmarkdown_2.25 desc_1.4.2
[173] fastICA_1.2-3 munsell_0.5.0 GetoptLong_1.0.5 GenomeInfoDbData_1.2.9
[177] iterators_1.0.14 reshape2_1.4.4 gtable_0.3.4

[RaredonLab]

I think that this is might be due to a cross-compatibility issue with Seurat v5. We are working to patch this currently. Please try installing NICHES using the "dev_master" branch and see if this fixes the issue.

Sam

[lnbooth]

Thank you! The dev_master install fixed the issue for me.