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Error with MetaspotsByGroups and ConstructMetaspots #250

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liuxiawei opened this issue Mar 29, 2024 · 4 comments
Open

Error with MetaspotsByGroups and ConstructMetaspots #250

liuxiawei opened this issue Mar 29, 2024 · 4 comments

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@liuxiawei
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Describe the bug
When I use MetaspotsByGroups to treat my seurat_obj, It reports error. Looks like follow:

Not validating Seurat objectsNot validating Seurat objectsNot validating Seurat objectsNot validating Seurat objectsNot validating Seurat objectsError in array(x, c(length(x), 1L), if (!is.null(names(x))) list(names(x),  : 
  'data'must be a vector, not 'NULL'
收捲时出错: 'length = 140' in coercion to 'logical(1)'
Error: no more error handlers available (recursive errors?); invoking 'abort' restart

After I tired to debug. I found the problem may be from followed code (

hdWGCNA/R/Metaspots.R

Line 80 in b3b5acf

tmp <- lapply(1:length(col_bounds), function(i){
) :
图片

In my test, I always get empty element with cur_coords
Sadly, It's so hard for me to deeply debug , I hope I could run this app.

seurat_obj<-some_seurat_for_10x
# make a dataframe containing the image coordinates for each sample
image_df <- do.call(rbind, lapply(names(seurat_obj@images), function(x){
  seurat_obj@images[[x]]@coordinates
}))

# merge the image_df with the Seurat metadata
new_meta <- merge([email protected], image_df, by='row.names')

# fix the row ordering to match the original seurat object
rownames(new_meta) <- new_meta$Row.names
ix <- match(as.character(colnames(seurat_obj)), as.character(rownames(new_meta)))
new_meta <- new_meta[ix,]

# add the new metadata to the seurat object
[email protected] <- new_meta

head(image_df)
seurat_obj <- seurat_obj %>%
  NormalizeData() %>%
  FindVariableFeatures() %>%
  ScaleData() %>%
  RunPCA()

# Louvain clustering and umap
seurat_obj <- FindNeighbors(seurat_obj, dims = 1:30)
seurat_obj <- FindClusters(seurat_obj,verbose = TRUE)
seurat_obj <- RunUMAP(seurat_obj, dims = 1:30)

# set factor level for anterior / posterior
# seurat_mouse_vis$region <- factor(as.character(seurat_mouse_vis$region), levels=c('anterior', 'posterior'))

# show the UMAP
p1 <- DimPlot(seurat_obj, label=TRUE, reduction = "umap", group.by = "seurat_clusters") + NoLegend()
p1
Idents(seurat_obj) <- seurat_obj$seurat_clusters

seurat_obj <- SetupForWGCNA(
  seurat_obj,
  # gene_select = "fraction",
  # fraction = 0.05,
  wgcna_name = "vis"
)

seurat_obj <-  MetaspotsByGroups(seurat_obj)

R session info

> devtools::session_info()
─ Session info ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
 setting  value
 version  R version 4.3.1 (2023-06-16)
 os       UnionTech OS Desktop 20 Home
 system   x86_64, linux-gnu
 ui       RStudio
 language zh_CN
 collate  C.UTF-8
 ctype    C.UTF-8
 tz       Asia/Beijing
 date     2024-03-29
 rstudio  1.1.456 (desktop)
 pandoc   2.12 @ /home/liuxiawei/micromamba/envs/r/bin/ (via rmarkdown)

─ Packages ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
 package              * version    date (UTC) lib source
 abind                  1.4-5      2016-07-21 [1] CRAN (R 4.3.1)
 AnnotationDbi          1.64.1     2023-11-03 [1] Bioconductor
 ape                    5.7-1      2023-03-13 [1] CRAN (R 4.3.1)
 assertthat             0.2.1      2019-03-21 [1] CRAN (R 4.3.1)
 backports              1.4.1      2021-12-13 [1] CRAN (R 4.3.1)
 base64enc              0.1-3      2015-07-28 [1] CRAN (R 4.3.1)
 beeswarm               0.4.0      2021-06-01 [1] CRAN (R 4.3.1)
 biglm                  0.9-2.1    2020-11-27 [1] CRAN (R 4.3.1)
 Biobase              * 2.62.0     2023-10-24 [1] Bioconductor
 BiocGenerics         * 0.48.1     2023-11-01 [1] Bioconductor
 BiocManager            1.30.22    2023-08-08 [1] CRAN (R 4.3.1)
 BiocParallel         * 1.36.0     2023-10-24 [1] Bioconductor
 Biostrings             2.70.1     2023-10-25 [1] Bioconductor
 bit                    4.0.5      2022-11-15 [1] CRAN (R 4.3.1)
 bit64                  4.0.5      2020-08-30 [1] CRAN (R 4.3.1)
 bitops                 1.0-7      2021-04-24 [1] CRAN (R 4.3.1)
 blob                   1.2.4      2023-03-17 [1] CRAN (R 4.3.1)
 boot                   1.3-30     2024-02-26 [1] CRAN (R 4.3.1)
 broom                  1.0.5      2023-06-09 [1] CRAN (R 4.3.1)
 bslib                  0.6.1      2023-11-28 [1] CRAN (R 4.3.1)
 cachem                 1.0.8      2023-05-01 [1] CRAN (R 4.3.1)
 callr                  3.7.5      2024-02-19 [1] CRAN (R 4.3.2)
 car                    3.1-2      2023-03-30 [1] CRAN (R 4.3.1)
 carData                3.0-5      2022-01-06 [1] CRAN (R 4.3.1)
 Cardinal             * 3.4.3      2023-11-23 [1] Bioconductor 3.18 (R 4.3.1)
 CardinalIO             1.0.0      2023-10-24 [1] Bioconductor
 checkmate              2.3.1      2023-12-04 [1] CRAN (R 4.3.1)
 class                  7.3-22     2023-05-03 [1] CRAN (R 4.3.1)
 classInt               0.4-10     2023-09-05 [1] CRAN (R 4.3.1)
 cli                    3.6.2      2023-12-11 [1] CRAN (R 4.3.2)
 cluster                2.1.6      2023-12-01 [1] CRAN (R 4.3.1)
 codetools              0.2-19     2023-02-01 [1] CRAN (R 4.3.1)
 colorspace             2.1-0      2023-01-23 [1] CRAN (R 4.3.1)
 confintr               1.0.2      2023-06-04 [1] CRAN (R 4.3.1)
 cowplot              * 1.1.3      2024-01-22 [1] CRAN (R 4.3.1)
 crayon                 1.5.2      2022-09-29 [1] CRAN (R 4.3.1)
 crosstalk              1.2.1      2023-11-23 [1] CRAN (R 4.3.1)
 curl                   5.2.1      2024-03-01 [1] CRAN (R 4.3.1)
 data.table             1.15.2     2024-02-29 [1] CRAN (R 4.3.1)
 DBI                    1.2.2      2024-02-16 [1] CRAN (R 4.3.2)
 dbscan                 1.1-12     2023-11-28 [1] CRAN (R 4.3.1)
 DelayedArray           0.28.0     2023-10-24 [1] Bioconductor
 DelayedMatrixStats     1.24.0     2023-10-24 [1] Bioconductor
 deldir                 2.0-4      2024-02-28 [1] CRAN (R 4.3.1)
 desc                   1.4.3      2023-12-10 [1] CRAN (R 4.3.2)
 devtools               2.4.5      2022-10-11 [1] CRAN (R 4.3.1)
 digest                 0.6.35     2024-03-11 [1] CRAN (R 4.3.1)
 doParallel             1.0.17     2022-02-07 [1] CRAN (R 4.3.1)
 dotCall64              1.1-1      2023-11-28 [1] CRAN (R 4.3.1)
 dplyr                * 1.1.4      2023-11-17 [1] CRAN (R 4.3.2)
 dynamicTreeCut       * 1.63-1     2016-03-11 [1] CRAN (R 4.3.1)
 e1071                  1.7-14     2023-12-06 [1] CRAN (R 4.3.2)
 EBImage              * 4.44.0     2023-10-24 [1] Bioconductor
 ellipsis               0.3.2      2021-04-29 [1] CRAN (R 4.3.1)
 evaluate               0.23       2023-11-01 [1] CRAN (R 4.3.1)
 fansi                  1.0.6      2023-12-08 [1] CRAN (R 4.3.1)
 farver                 2.1.1      2022-07-06 [1] CRAN (R 4.3.1)
 fastcluster          * 1.2.6      2024-01-12 [1] CRAN (R 4.3.1)
 fastDummies            1.7.3      2023-07-06 [1] CRAN (R 4.3.1)
 fastmap                1.1.1      2023-02-24 [1] CRAN (R 4.3.1)
 fftwtools              0.9-11     2021-03-01 [1] CRAN (R 4.3.1)
 fitdistrplus           1.1-11     2023-04-25 [1] CRAN (R 4.3.1)
 FNN                    1.1.4      2024-01-12 [1] CRAN (R 4.3.1)
 forcats              * 1.0.0      2023-01-29 [1] CRAN (R 4.3.1)
 foreach                1.5.2      2022-02-02 [1] CRAN (R 4.3.1)
 foreign                0.8-86     2023-11-28 [1] CRAN (R 4.3.1)
 Formula                1.2-5      2023-02-24 [1] CRAN (R 4.3.1)
 fs                     1.6.3      2023-07-20 [1] CRAN (R 4.3.1)
 future                 1.33.1     2023-12-22 [1] CRAN (R 4.3.2)
 future.apply           1.11.1     2023-12-21 [1] CRAN (R 4.3.2)
 generics               0.1.3      2022-07-05 [1] CRAN (R 4.3.1)
 GenomeInfoDb         * 1.38.8     2024-03-15 [1] Bioconductor 3.18 (R 4.3.1)
 GenomeInfoDbData       1.2.11     2024-03-20 [1] Bioconductor
 GenomicRanges        * 1.54.1     2023-10-29 [1] Bioconductor
 ggbeeswarm             0.7.2      2023-04-29 [1] CRAN (R 4.3.1)
 ggplot2              * 3.5.0      2024-02-23 [1] CRAN (R 4.3.1)
 ggpmisc              * 0.5.5      2023-11-15 [1] CRAN (R 4.3.1)
 ggpp                 * 0.5.6      2024-01-09 [1] CRAN (R 4.3.1)
 ggpubr               * 0.6.0      2023-02-10 [1] CRAN (R 4.3.1)
 ggrastr                1.0.2      2023-06-01 [1] CRAN (R 4.3.1)
 ggrepel              * 0.9.5      2024-01-10 [1] CRAN (R 4.3.1)
 ggridges               0.5.6      2024-01-23 [1] CRAN (R 4.3.1)
 ggsignif               0.6.4      2022-10-13 [1] CRAN (R 4.3.1)
 glmGamPoi              1.14.3     2024-02-11 [1] Bioconductor 3.18 (R 4.3.1)
 globals                0.16.3     2024-03-08 [1] CRAN (R 4.3.3)
 glue                   1.7.0      2024-01-09 [1] CRAN (R 4.3.1)
 GO.db                  3.18.0     2024-03-25 [1] Bioconductor
 goftest                1.2-3      2021-10-07 [1] CRAN (R 4.3.1)
 gridExtra              2.3        2017-09-09 [1] CRAN (R 4.3.1)
 grr                    0.9.5      2016-08-26 [1] CRAN (R 4.3.1)
 gtable                 0.3.4      2023-08-21 [1] CRAN (R 4.3.1)
 harmony              * 1.2.0      2023-11-29 [1] CRAN (R 4.3.1)
 hdf5r                  1.3.10     2024-03-02 [1] CRAN (R 4.3.1)
 hdWGCNA              * 0.3.01     2024-03-29 [1] Github (smorabit/hdWGCNA@b3b5acf)
 Hmisc                  5.1-2      2024-03-11 [1] CRAN (R 4.3.1)
 hms                    1.1.3      2023-03-21 [1] CRAN (R 4.3.1)
 htmlTable              2.4.2      2023-10-29 [1] CRAN (R 4.3.1)
 htmltools              0.5.7      2023-11-03 [1] CRAN (R 4.3.1)
 htmlwidgets            1.6.4      2023-12-06 [1] CRAN (R 4.3.1)
 httpuv                 1.6.14     2024-01-26 [1] CRAN (R 4.3.1)
 httr                   1.4.7      2023-08-15 [1] CRAN (R 4.3.1)
 ica                    1.0-3      2022-07-08 [1] CRAN (R 4.3.1)
 igraph               * 2.0.3      2024-03-13 [1] CRAN (R 4.3.1)
 impute                 1.76.0     2023-10-24 [1] Bioconductor
 IRanges              * 2.36.0     2023-10-24 [1] Bioconductor
 irlba                  2.3.5.1    2022-10-03 [1] CRAN (R 4.3.1)
 iterators              1.0.14     2022-02-05 [1] CRAN (R 4.3.1)
 jpeg                   0.1-10     2022-11-29 [1] CRAN (R 4.3.1)
 jquerylib              0.1.4      2021-04-26 [1] CRAN (R 4.3.1)
 jsonlite               1.8.8      2023-12-04 [1] CRAN (R 4.3.1)
 KEGGREST               1.42.0     2023-10-24 [1] Bioconductor
 KernSmooth             2.23-22    2023-07-10 [1] CRAN (R 4.3.1)
 knitr                  1.45       2023-10-30 [1] CRAN (R 4.3.1)
 labeling               0.4.3      2023-08-29 [1] CRAN (R 4.3.1)
 later                  1.3.2      2023-12-06 [1] CRAN (R 4.3.1)
 lattice                0.22-6     2024-03-20 [1] CRAN (R 4.3.1)
 lazyeval               0.2.2      2019-03-15 [1] CRAN (R 4.3.1)
 leiden                 0.4.3.1    2023-11-17 [1] CRAN (R 4.3.1)
 leidenbase             0.1.27     2023-12-01 [1] CRAN (R 4.3.1)
 lifecycle              1.0.4      2023-11-07 [1] CRAN (R 4.3.2)
 limma                  3.58.1     2023-10-31 [1] Bioconductor
 listenv                0.9.1      2024-01-29 [1] CRAN (R 4.3.1)
 lme4                   1.1-35.1   2023-11-05 [1] CRAN (R 4.3.1)
 lmodel2                1.7-3      2018-02-05 [1] CRAN (R 4.3.1)
 lmtest                 0.9-40     2022-03-21 [1] CRAN (R 4.3.1)
 locfit                 1.5-9.9    2024-03-01 [1] CRAN (R 4.3.1)
 lubridate            * 1.9.3      2023-09-27 [1] CRAN (R 4.3.1)
 magick               * 2.7.5      2023-08-07 [1] CRAN (R 4.3.1)
 magrittr             * 2.0.3      2022-03-30 [1] CRAN (R 4.3.1)
 MASS                   7.3-60.0.1 2024-01-13 [1] CRAN (R 4.3.1)
 Matrix                 1.6-5      2024-01-11 [1] CRAN (R 4.3.1)
 MatrixGenerics       * 1.14.0     2023-10-24 [1] Bioconductor
 MatrixModels           0.5-3      2023-11-06 [1] CRAN (R 4.3.1)
 matrixStats          * 1.2.0      2023-12-11 [1] CRAN (R 4.3.1)
 matter                 2.4.1      2024-03-13 [1] Bioconductor 3.18 (R 4.3.1)
 mclust                 6.1        2024-02-23 [1] CRAN (R 4.3.1)
 memoise                2.0.1      2021-11-26 [1] CRAN (R 4.3.1)
 mgcv                   1.9-1      2023-12-21 [1] CRAN (R 4.3.1)
 mime                   0.12       2021-09-28 [1] CRAN (R 4.3.1)
 miniUI                 0.1.1.1    2018-05-18 [1] CRAN (R 4.3.1)
 minqa                  1.2.6      2023-09-11 [1] CRAN (R 4.3.1)
 monocle3             * 1.3.1      2023-11-09 [1] Bioconductor
 munsell                0.5.0      2018-06-12 [1] CRAN (R 4.3.1)
 nlme                   3.1-164    2023-11-27 [1] CRAN (R 4.3.1)
 nloptr                 2.0.3      2022-05-26 [1] CRAN (R 4.3.1)
 nnet                   7.3-19     2023-05-03 [1] CRAN (R 4.3.1)
 ontologyIndex          2.12       2024-02-27 [1] CRAN (R 4.3.1)
 parallelly             1.37.1     2024-02-29 [1] CRAN (R 4.3.1)
 patchwork            * 1.2.0      2024-01-08 [1] CRAN (R 4.3.1)
 pbapply                1.7-2      2023-06-27 [1] CRAN (R 4.3.1)
 pbmcapply              1.5.1      2022-04-28 [1] CRAN (R 4.3.1)
 pheatmap               1.0.12     2019-01-04 [1] CRAN (R 4.3.1)
 pillar                 1.9.0      2023-03-22 [1] CRAN (R 4.3.1)
 pkgbuild               1.4.4      2024-03-17 [1] CRAN (R 4.3.1)
 pkgconfig              2.0.3      2019-09-22 [1] CRAN (R 4.3.1)
 pkgload                1.3.4      2024-01-16 [1] CRAN (R 4.3.1)
 plotly               * 4.10.4     2024-01-13 [1] CRAN (R 4.3.1)
 plyr                   1.8.9      2023-10-02 [1] CRAN (R 4.3.1)
 png                    0.1-8      2022-11-29 [1] CRAN (R 4.3.1)
 polyclip               1.10-6     2023-09-27 [1] CRAN (R 4.3.1)
 polynom                1.4-1      2022-04-11 [1] CRAN (R 4.3.1)
 preprocessCore         1.64.0     2023-10-24 [1] Bioconductor
 processx               3.8.4      2024-03-16 [1] CRAN (R 4.3.1)
 profvis                0.3.8      2023-05-02 [1] CRAN (R 4.3.1)
 progressr              0.14.0     2023-08-10 [1] CRAN (R 4.3.1)
 promises               1.2.1      2023-08-10 [1] CRAN (R 4.3.1)
 ProtGenerics         * 1.34.0     2023-10-24 [1] Bioconductor
 proxy                  0.4-27     2022-06-09 [1] CRAN (R 4.3.1)
 ps                     1.7.6      2024-01-18 [1] CRAN (R 4.3.1)
 purrr                * 1.0.2      2023-08-10 [1] CRAN (R 4.3.1)
 quantreg               5.97       2023-08-19 [1] CRAN (R 4.3.1)
 R.methodsS3            1.8.2      2022-06-13 [1] CRAN (R 4.3.1)
 R.oo                   1.26.0     2024-01-24 [1] CRAN (R 4.3.1)
 R.utils                2.12.3     2023-11-18 [1] CRAN (R 4.3.1)
 R6                     2.5.1      2021-08-19 [1] CRAN (R 4.3.1)
 ragg                   1.2.6      2023-10-10 [1] CRAN (R 4.3.1)
 RANN                   2.6.1      2019-01-08 [1] CRAN (R 4.3.1)
 RColorBrewer           1.1-3      2022-04-03 [1] CRAN (R 4.3.1)
 Rcpp                 * 1.0.12     2024-01-09 [1] CRAN (R 4.3.1)
 RcppAnnoy              0.0.22     2024-01-23 [1] CRAN (R 4.3.1)
 RcppHNSW               0.6.0      2024-02-04 [1] CRAN (R 4.3.1)
 RCurl                  1.98-1.14  2024-01-09 [1] CRAN (R 4.3.1)
 readr                * 2.1.5      2024-01-10 [1] CRAN (R 4.3.1)
 remotes                2.5.0      2024-03-17 [1] CRAN (R 4.3.1)
 reshape2               1.4.4      2020-04-09 [1] CRAN (R 4.3.1)
 reticulate             1.35.0     2024-01-31 [1] CRAN (R 4.3.1)
 rlang                  1.1.3      2024-01-10 [1] CRAN (R 4.3.1)
 rmarkdown              2.26       2024-03-05 [1] CRAN (R 4.3.1)
 ROCR                   1.0-11     2020-05-02 [1] CRAN (R 4.3.1)
 rpart                  4.1.23     2023-12-05 [1] CRAN (R 4.3.1)
 RSpectra               0.16-1     2022-04-24 [1] CRAN (R 4.3.1)
 RSQLite                2.3.1      2023-04-03 [1] CRAN (R 4.3.1)
 rstatix                0.7.2      2023-02-01 [1] CRAN (R 4.3.1)
 rstudioapi             0.15.0     2023-07-07 [1] CRAN (R 4.3.1)
 rsvd                   1.0.5      2021-04-16 [1] CRAN (R 4.3.1)
 Rtsne                  0.17       2023-12-07 [1] CRAN (R 4.3.1)
 s2                     1.1.6      2023-12-19 [1] CRAN (R 4.3.1)
 S4Arrays               1.2.1      2024-03-04 [1] Bioconductor 3.18 (R 4.3.1)
 S4Vectors            * 0.40.2     2023-11-23 [1] Bioconductor 3.18 (R 4.3.2)
 sass                   0.4.9      2024-03-15 [1] CRAN (R 4.3.1)
 scales               * 1.3.0      2023-11-28 [1] CRAN (R 4.3.1)
 scattermore            1.2        2023-06-12 [1] CRAN (R 4.3.1)
 sctransform            0.4.1      2023-10-19 [1] CRAN (R 4.3.1)
 semla                * 1.1.6      2024-03-28 [1] Github (ludvigla/semla@4ec7b9a)
 sessioninfo            1.2.2      2021-12-06 [1] CRAN (R 4.3.1)
 Seurat               * 5.0.3      2024-03-18 [1] CRAN (R 4.3.1)
 SeuratDisk           * 0.0.0.9021 2024-03-18 [1] Github (mojaveazure/seurat-disk@877d4e1)
 SeuratObject         * 5.0.1      2023-11-17 [1] CRAN (R 4.3.2)
 SeuratWrappers       * 0.3.4      2024-03-19 [1] Github (satijalab/seurat-wrappers@d9594f6)
 sf                     1.0-14     2023-07-11 [1] CRAN (R 4.3.0)
 shiny                  1.8.0      2023-11-17 [1] CRAN (R 4.3.1)
 shinyjs                2.1.0      2021-12-23 [1] CRAN (R 4.3.1)
 signal                 1.8-0      2023-11-27 [1] CRAN (R 4.3.1)
 SingleCellExperiment * 1.24.0     2023-10-24 [1] Bioconductor
 slam                   0.1-50     2022-01-08 [1] CRAN (R 4.3.1)
 sp                   * 2.1-3      2024-01-30 [1] CRAN (R 4.3.2)
 spam                   2.10-0     2023-10-23 [1] CRAN (R 4.3.1)
 SparseArray            1.2.4      2024-02-11 [1] Bioconductor 3.18 (R 4.3.1)
 SparseM                1.81       2021-02-18 [1] CRAN (R 4.3.1)
 sparseMatrixStats      1.14.0     2023-10-24 [1] Bioconductor
 spatstat.data          3.0-4      2024-01-15 [1] CRAN (R 4.3.2)
 spatstat.explore       3.2-6      2024-02-01 [1] CRAN (R 4.3.2)
 spatstat.geom          3.2-9      2024-02-28 [1] CRAN (R 4.3.2)
 spatstat.random        3.2-3      2024-02-29 [1] CRAN (R 4.3.3)
 spatstat.sparse        3.0-3      2023-10-24 [1] CRAN (R 4.3.1)
 spatstat.utils         3.0-4      2023-10-24 [1] CRAN (R 4.3.1)
 spData                 2.3.0      2023-07-06 [1] CRAN (R 4.3.1)
 spdep                  1.3-3      2024-02-07 [1] CRAN (R 4.3.1)
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@smorabit
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smorabit commented Apr 3, 2024

Hello,

Are you able to reproduce this error on the tutorial dataset? I tried and I am not able to. It is very difficult for me to help resolve issues unless I can reproduce the error on my side.

@liuxiawei
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I'm very sad that the demo code is running right way. This is my seurat object. Could you please help to check it ?

str(ta_obj)
Formal class 'Seurat' [package "SeuratObject"] with 13 slots
  ..@ assays      :List of 2
  .. ..$ Spatial:Formal class 'Assay' [package "SeuratObject"] with 8 slots
  .. .. .. ..@ counts       :Formal class 'dgCMatrix' [package "Matrix"] with 6 slots
  .. .. .. .. .. ..@ i       : int [1:469954] 350 2731 3006 4777 8380 8959 10973 12171 13098 14525 ...
  .. .. .. .. .. ..@ p       : int [1:492] 0 21 605 2046 2601 2931 4209 6214 7711 7774 ...
  .. .. .. .. .. ..@ Dim     : int [1:2] 20092 491
  .. .. .. .. .. ..@ Dimnames:List of 2
  .. .. .. .. .. .. ..$ : chr [1:20092] "Gene0000010" "Gene0000020" "Gene0000030" "Gene0000040" ...
  .. .. .. .. .. .. ..$ : chr [1:491] "36077725294100" "36077725294200" "36077725294300" "36077725294400" ...
  .. .. .. .. .. ..@ x       : num [1:469954] 1 1 1 1 1 1 1 2 1 4 ...
  .. .. .. .. .. ..@ factors : list()
  .. .. .. ..@ data         :Formal class 'dgCMatrix' [package "Matrix"] with 6 slots
  .. .. .. .. .. ..@ i       : int [1:469954] 350 2731 3006 4777 8380 8959 10973 12171 13098 14525 ...
  .. .. .. .. .. ..@ p       : int [1:492] 0 21 605 2046 2601 2931 4209 6214 7711 7774 ...
  .. .. .. .. .. ..@ Dim     : int [1:2] 20092 491
  .. .. .. .. .. ..@ Dimnames:List of 2
  .. .. .. .. .. .. ..$ : chr [1:20092] "Gene0000010" "Gene0000020" "Gene0000030" "Gene0000040" ...
  .. .. .. .. .. .. ..$ : chr [1:491] "36077725294100" "36077725294200" "36077725294300" "36077725294400" ...
  .. .. .. .. .. ..@ x       : num [1:469954] 5.75 5.75 5.75 5.75 5.75 ...
  .. .. .. .. .. ..@ factors : list()
  .. .. .. ..@ scale.data   : num[0 , 0 ] 
  .. .. .. ..@ assay.orig   : NULL
  .. .. .. ..@ var.features : chr(0) 
  .. .. .. ..@ meta.features:'data.frame':	20092 obs. of  3 variables:
  .. .. .. .. ..$ n_cells : int [1:20092] 55 22 55 222 99 26 50 157 106 15 ...
  .. .. .. .. ..$ n_counts: int [1:20092] 92 36 86 415 167 49 73 280 171 21 ...
  .. .. .. .. ..$ mean_umi: num [1:20092] 1.67 1.64 1.56 1.87 1.69 ...
  .. .. .. ..@ misc         : Named list()
  .. .. .. ..@ key          : chr "spatial_"
  .. ..$ SCT    :Formal class 'SCTAssay' [package "Seurat"] with 9 slots
  .. .. .. ..@ SCTModel.list:List of 1
  .. .. .. .. ..$ model1:Formal class 'SCTModel' [package "Seurat"] with 7 slots
  .. .. .. .. .. .. ..@ feature.attributes:'data.frame':	12084 obs. of  12 variables:
  .. .. .. .. .. .. .. ..$ detection_rate       : num [1:12084] 0.053 0.0244 0.0489 0.2424 0.0998 ...
  .. .. .. .. .. .. .. ..$ gmean                : num [1:12084] 0.0538 0.0239 0.0428 0.2671 0.1037 ...
  .. .. .. .. .. .. .. ..$ variance             : num [1:12084] 0.288 0.09 0.132 0.925 0.421 ...
  .. .. .. .. .. .. .. ..$ residual_mean        : num [1:12084] 0.01555 -0.00331 -0.00583 0.00322 -0.00609 ...
  .. .. .. .. .. .. .. ..$ residual_variance    : num [1:12084] 1.125 0.411 0.603 1.014 0.827 ...
  .. .. .. .. .. .. .. ..$ theta                : num [1:12084] 0.0847 0.0384 0.0681 0.337 0.1509 ...
  .. .. .. .. .. .. .. ..$ (Intercept)          : num [1:12084] -10.86 -11.67 -11.09 -9.26 -10.19 ...
  .. .. .. .. .. .. .. ..$ log_umi              : num [1:12084] 2.3 2.3 2.3 2.3 2.3 ...
  .. .. .. .. .. .. .. ..$ genes_log_gmean_step1: logi [1:12084] FALSE TRUE FALSE FALSE FALSE FALSE ...
  .. .. .. .. .. .. .. ..$ step1_theta          : num [1:12084] NA 0.0393 NA NA NA ...
  .. .. .. .. .. .. .. ..$ step1_(Intercept)    : num [1:12084] NA -11.8 NA NA NA ...
  .. .. .. .. .. .. .. ..$ step1_log_umi        : num [1:12084] NA 2.3 NA NA NA ...
  .. .. .. .. .. .. ..@ cell.attributes   :'data.frame':	491 obs. of  3 variables:
  .. .. .. .. .. .. .. ..$ umi        : num [1:491] 32 2966 7874 2277 1121 ...
  .. .. .. .. .. .. .. ..$ log_umi    : num [1:491] 1.51 3.47 3.9 3.36 3.05 ...
  .. .. .. .. .. .. .. ..$ cells_step1: logi [1:491] TRUE TRUE TRUE TRUE TRUE TRUE ...
  .. .. .. .. .. .. ..@ clips             :List of 2
  .. .. .. .. .. .. .. ..$ vst: num [1:2] -22.2 22.2
  .. .. .. .. .. .. .. ..$ sct: num [1:2] -4.05 4.05
  .. .. .. .. .. .. ..@ umi.assay         : chr "Spatial"
  .. .. .. .. .. .. ..@ model             : chr "y ~ log_umi"
  .. .. .. .. .. .. ..@ arguments         :List of 33
  .. .. .. .. .. .. .. ..$ glmGamPoi_check          : logi TRUE
  .. .. .. .. .. .. .. ..$ latent_var               : chr "log_umi"
  .. .. .. .. .. .. .. ..$ batch_var                : NULL
  .. .. .. .. .. .. .. ..$ latent_var_nonreg        : NULL
  .. .. .. .. .. .. .. ..$ n_genes                  : num 2000
  .. .. .. .. .. .. .. ..$ n_cells                  : num 491
  .. .. .. .. .. .. .. ..$ method                   : chr "glmGamPoi_offset"
  .. .. .. .. .. .. .. ..$ do_regularize            : logi TRUE
  .. .. .. .. .. .. .. ..$ theta_regularization     : chr "od_factor"
  .. .. .. .. .. .. .. ..$ res_clip_range           : num [1:2] -22.2 22.2
  .. .. .. .. .. .. .. ..$ bin_size                 : num 500
  .. .. .. .. .. .. .. ..$ min_cells                : num 5
  .. .. .. .. .. .. .. ..$ residual_type            : chr "pearson"
  .. .. .. .. .. .. .. ..$ return_cell_attr         : logi TRUE
  .. .. .. .. .. .. .. ..$ return_gene_attr         : logi TRUE
  .. .. .. .. .. .. .. ..$ return_corrected_umi     : logi TRUE
  .. .. .. .. .. .. .. ..$ min_variance             : chr "umi_median"
  .. .. .. .. .. .. .. ..$ bw_adjust                : num 3
  .. .. .. .. .. .. .. ..$ gmean_eps                : num 1
  .. .. .. .. .. .. .. ..$ theta_estimation_fun     : chr "theta.ml"
  .. .. .. .. .. .. .. ..$ theta_given              : NULL
  .. .. .. .. .. .. .. ..$ exclude_poisson          : logi TRUE
  .. .. .. .. .. .. .. ..$ use_geometric_mean       : logi TRUE
  .. .. .. .. .. .. .. ..$ use_geometric_mean_offset: logi FALSE
  .. .. .. .. .. .. .. ..$ fix_intercept            : logi FALSE
  .. .. .. .. .. .. .. ..$ fix_slope                : logi FALSE
  .. .. .. .. .. .. .. ..$ scale_factor             : logi NA
  .. .. .. .. .. .. .. ..$ vst.flavor               : chr "v2"
  .. .. .. .. .. .. .. ..$ verbosity                : num 0
  .. .. .. .. .. .. .. ..$ verbose                  : NULL
  .. .. .. .. .. .. .. ..$ show_progress            : NULL
  .. .. .. .. .. .. .. ..$ set_min_var              : num 0.16
  .. .. .. .. .. .. .. ..$ sct.clip.range           : num [1:2] -4.05 4.05
  .. .. .. .. .. .. ..@ median_umi        : num 4153
  .. .. .. ..@ counts       :Formal class 'dgCMatrix' [package "Matrix"] with 6 slots
  .. .. .. .. .. ..@ i       : int [1:429533] 14 61 73 107 147 187 192 223 244 250 ...
  .. .. .. .. .. ..@ p       : int [1:492] 0 644 1219 2551 3098 3508 4745 6165 7529 8150 ...
  .. .. .. .. .. ..@ Dim     : int [1:2] 12084 491
  .. .. .. .. .. ..@ Dimnames:List of 2
  .. .. .. .. .. .. ..$ : chr [1:12084] "Gene0000010" "Gene0000020" "Gene0000030" "Gene0000040" ...
  .. .. .. .. .. .. ..$ : chr [1:491] "36077725294100" "36077725294200" "36077725294300" "36077725294400" ...
  .. .. .. .. .. ..@ x       : num [1:429533] 10 3 2 5 1 1 1 1 4 1 ...
  .. .. .. .. .. ..@ factors : list()
  .. .. .. ..@ data         :Formal class 'dgCMatrix' [package "Matrix"] with 6 slots
  .. .. .. .. .. ..@ i       : int [1:429533] 14 61 73 107 147 187 192 223 244 250 ...
  .. .. .. .. .. ..@ p       : int [1:492] 0 644 1219 2551 3098 3508 4745 6165 7529 8150 ...
  .. .. .. .. .. ..@ Dim     : int [1:2] 12084 491
  .. .. .. .. .. ..@ Dimnames:List of 2
  .. .. .. .. .. .. ..$ : chr [1:12084] "Gene0000010" "Gene0000020" "Gene0000030" "Gene0000040" ...
  .. .. .. .. .. .. ..$ : chr [1:491] "36077725294100" "36077725294200" "36077725294300" "36077725294400" ...
  .. .. .. .. .. ..@ x       : num [1:429533] 3.54 2.4 2.04 2.87 1.47 ...
  .. .. .. .. .. ..@ factors : list()
  .. .. .. ..@ scale.data   : num [1:2000, 1:491] -0.212 -0.504 -0.386 -0.251 0.41 ...
  .. .. .. .. ..- attr(*, "dimnames")=List of 2
  .. .. .. .. .. ..$ : chr [1:2000] "Gene0000010" "Gene0000040" "Gene0000080" "Gene0000130" ...
  .. .. .. .. .. ..$ : chr [1:491] "36077725294100" "36077725294200" "36077725294300" "36077725294400" ...
  .. .. .. ..@ assay.orig   : chr "Spatial"
  .. .. .. ..@ var.features : chr [1:2000] "Gene0062990" "Gene0061940" "Gene0118390" "Gene0327200" ...
  .. .. .. ..@ meta.features:'data.frame':	12084 obs. of  0 variables
  .. .. .. ..@ misc         : Named list()
  .. .. .. ..@ key          : chr "sct_"
  ..@ meta.data   :'data.frame':	491 obs. of  18 variables:
  .. ..$ Row.names       : 'AsIs' chr [1:491] "36077725294100" "36077725294200" "36077725294300" "36077725294400" ...
  .. ..$ _index          : chr [1:491] "36077725294100" "36077725294200" "36077725294300" "36077725294400" ...
  .. ..$ nCount_Spatial  : num [1:491] 32 2966 7874 2277 1121 ...
  .. ..$ nFeature_Spatial: int [1:491] 21 584 1441 555 330 1278 2005 1497 63 391 ...
  .. ..$ orig.ident      : chr [1:491] "A" "A" "A" "A" ...
  .. ..$ percent.mito    : num [1:491] 0 0 0 0 0 0 0 0 0 0 ...
  .. ..$ x               : int [1:491] 8400 8400 8400 8400 8500 8500 8500 8500 8600 8600 ...
  .. ..$ y               : int [1:491] 7700 7800 7900 8000 7700 7800 7900 8000 6700 6800 ...
  .. ..$ nCount_SCT      : num [1:491] 2995 3923 4438 3790 3493 ...
  .. ..$ nFeature_SCT    : int [1:491] 644 575 1332 547 410 1237 1420 1364 621 446 ...
  .. ..$ SCT_snn_res.1.2 : Factor w/ 7 levels "0","1","2","3",..: 2 5 1 1 2 1 1 1 2 2 ...
  .. ..$ seurat_clusters : Factor w/ 5 levels "0","1","2","3",..: 5 1 1 1 3 1 1 1 5 1 ...
  .. ..$ tissue          : num [1:491] 1 1 1 1 1 1 1 1 1 1 ...
  .. ..$ row             : num [1:491] 5201 5301 5401 5501 5201 ...
  .. ..$ col             : num [1:491] 3201 3201 3201 3201 3301 ...
  .. ..$ imagerow        : num [1:491] 5201 5301 5401 5501 5201 ...
  .. ..$ imagecol        : num [1:491] 3201 3201 3201 3201 3301 ...
  .. ..$ SCT_snn_res.0.8 : Factor w/ 5 levels "0","1","2","3",..: 5 1 1 1 3 1 1 1 5 1 ...
  ..@ active.assay: chr "SCT"
  ..@ active.ident: Factor w/ 5 levels "0","1","2","3",..: 5 1 1 1 3 1 1 1 5 1 ...
  .. ..- attr(*, "names")= chr [1:491] "36077725294100" "36077725294200" "36077725294300" "36077725294400" ...
  ..@ graphs      :List of 2
  .. ..$ SCT_nn :Formal class 'Graph' [package "SeuratObject"] with 7 slots
  .. .. .. ..@ assay.used: chr "SCT"
  .. .. .. ..@ i         : int [1:9820] 0 8 37 54 74 95 234 235 236 237 ...
  .. .. .. ..@ p         : int [1:492] 0 21 55 62 74 138 159 168 183 210 ...
  .. .. .. ..@ Dim       : int [1:2] 491 491
  .. .. .. ..@ Dimnames  :List of 2
  .. .. .. .. ..$ : chr [1:491] "36077725294100" "36077725294200" "36077725294300" "36077725294400" ...
  .. .. .. .. ..$ : chr [1:491] "36077725294100" "36077725294200" "36077725294300" "36077725294400" ...
  .. .. .. ..@ x         : num [1:9820] 1 1 1 1 1 1 1 1 1 1 ...
  .. .. .. ..@ factors   : list()
  .. ..$ SCT_snn:Formal class 'Graph' [package "SeuratObject"] with 7 slots
  .. .. .. ..@ assay.used: chr "SCT"
  .. .. .. ..@ i         : int [1:39087] 0 8 12 15 16 37 54 74 95 117 ...
  .. .. .. ..@ p         : int [1:492] 0 32 143 229 344 431 534 586 647 679 ...
  .. .. .. ..@ Dim       : int [1:2] 491 491
  .. .. .. ..@ Dimnames  :List of 2
  .. .. .. .. ..$ : chr [1:491] "36077725294100" "36077725294200" "36077725294300" "36077725294400" ...
  .. .. .. .. ..$ : chr [1:491] "36077725294100" "36077725294200" "36077725294300" "36077725294400" ...
  .. .. .. ..@ x         : num [1:39087] 1 1 0.29 0.379 0.333 ...
  .. .. .. ..@ factors   : list()
  ..@ neighbors   : list()
  ..@ reductions  :List of 2
  .. ..$ pca :Formal class 'DimReduc' [package "SeuratObject"] with 9 slots
  .. .. .. ..@ cell.embeddings           : num [1:491, 1:50] -0.321 7.57 11.047 8.912 5.363 ...
  .. .. .. .. ..- attr(*, "dimnames")=List of 2
  .. .. .. .. .. ..$ : chr [1:491] "36077725294100" "36077725294200" "36077725294300" "36077725294400" ...
  .. .. .. .. .. ..$ : chr [1:50] "PC_1" "PC_2" "PC_3" "PC_4" ...
  .. .. .. ..@ feature.loadings          : num [1:2000, 1:50] -0.0706 -0.0691 -0.0804 -0.077 -0.0722 ...
  .. .. .. .. ..- attr(*, "dimnames")=List of 2
  .. .. .. .. .. ..$ : chr [1:2000] "Gene0062990" "Gene0061940" "Gene0118390" "Gene0327200" ...
  .. .. .. .. .. ..$ : chr [1:50] "PC_1" "PC_2" "PC_3" "PC_4" ...
  .. .. .. ..@ feature.loadings.projected: num[0 , 0 ] 
  .. .. .. ..@ assay.used                : chr "SCT"
  .. .. .. ..@ global                    : logi FALSE
  .. .. .. ..@ stdev                     : num [1:50] 8.38 7.7 4.84 4.04 3.89 ...
  .. .. .. ..@ jackstraw                 :Formal class 'JackStrawData' [package "SeuratObject"] with 4 slots
  .. .. .. .. .. ..@ empirical.p.values     : num[0 , 0 ] 
  .. .. .. .. .. ..@ fake.reduction.scores  : num[0 , 0 ] 
  .. .. .. .. .. ..@ empirical.p.values.full: num[0 , 0 ] 
  .. .. .. .. .. ..@ overall.p.values       : num[0 , 0 ] 
  .. .. .. ..@ misc                      :List of 1
  .. .. .. .. ..$ total.variance: num 1994
  .. .. .. ..@ key                       : chr "PC_"
  .. ..$ umap:Formal class 'DimReduc' [package "SeuratObject"] with 9 slots
  .. .. .. ..@ cell.embeddings           : num [1:491, 1:2] -4.518 -2.5526 -0.0788 -1.302 -3.5134 ...
  .. .. .. .. ..- attr(*, "scaled:center")= num [1:2] -7.54 -5.65
  .. .. .. .. ..- attr(*, "dimnames")=List of 2
  .. .. .. .. .. ..$ : chr [1:491] "36077725294100" "36077725294200" "36077725294300" "36077725294400" ...
  .. .. .. .. .. ..$ : chr [1:2] "umap_1" "umap_2"
  .. .. .. ..@ feature.loadings          : num[0 , 0 ] 
  .. .. .. ..@ feature.loadings.projected: num[0 , 0 ] 
  .. .. .. ..@ assay.used                : chr "SCT"
  .. .. .. ..@ global                    : logi TRUE
  .. .. .. ..@ stdev                     : num(0) 
  .. .. .. ..@ jackstraw                 :Formal class 'JackStrawData' [package "SeuratObject"] with 4 slots
  .. .. .. .. .. ..@ empirical.p.values     : num[0 , 0 ] 
  .. .. .. .. .. ..@ fake.reduction.scores  : num[0 , 0 ] 
  .. .. .. .. .. ..@ empirical.p.values.full: num[0 , 0 ] 
  .. .. .. .. .. ..@ overall.p.values       : num[0 , 0 ] 
  .. .. .. ..@ misc                      : list()
  .. .. .. ..@ key                       : chr "umap_"
  ..@ images      :List of 1
  .. ..$ slice1:Formal class 'VisiumV1' [package "Seurat"] with 6 slots
  .. .. .. ..@ image        : num [1:6101, 1:5901] 1 1 1 1 1 1 1 1 1 1 ...
  .. .. .. ..@ scale.factors:List of 4
  .. .. .. .. ..$ spot    : num 1
  .. .. .. .. ..$ fiducial: num 1
  .. .. .. .. ..$ hires   : num 1
  .. .. .. .. ..$ lowres  : num 1
  .. .. .. .. ..- attr(*, "class")= chr "scalefactors"
  .. .. .. ..@ coordinates  :'data.frame':	491 obs. of  5 variables:
  .. .. .. .. ..$ tissue  : num [1:491] 1 1 1 1 1 1 1 1 1 1 ...
  .. .. .. .. ..$ row     : num [1:491] 5201 5301 5401 5501 5201 ...
  .. .. .. .. ..$ col     : num [1:491] 3201 3201 3201 3201 3301 ...
  .. .. .. .. ..$ imagerow: num [1:491] 5201 5301 5401 5501 5201 ...
  .. .. .. .. ..$ imagecol: num [1:491] 3201 3201 3201 3201 3301 ...
  .. .. .. ..@ spot.radius  : num 0.000164
  .. .. .. ..@ assay        : chr "Spatial"
  .. .. .. ..@ key          : chr "slice1_"
  ..@ project.name: chr "AnnData"
  ..@ misc        :List of 6
  .. ..$ raw_cellname: chr [1:984] "22333829942000" "22333829942100" "22333829942200" "22333829942300" ...
  .. ..$ raw_counts  :Formal class 'dgCMatrix' [package "Matrix"] with 6 slots
  .. .. .. ..@ i       : int [1:965369] 14 77 92 142 218 272 350 405 492 560 ...
  .. .. .. ..@ p       : int [1:985] 0 253 936 1901 2909 3419 3465 3553 4323 5593 ...
  .. .. .. ..@ Dim     : int [1:2] 20092 984
  .. .. .. ..@ Dimnames:List of 2
  .. .. .. .. ..$ : NULL
  .. .. .. .. ..$ : NULL
  .. .. .. ..@ x       : num [1:965369] 3 1 1 1 1 1 2 1 3 1 ...
  .. .. .. ..@ factors : list()
  .. ..$ raw_genename: chr [1:20092] "Gene0000010" "Gene0000020" "Gene0000030" "Gene0000040" ...
  .. ..$ sn          :List of 3
  .. .. ..$ _index: int 0
  .. .. ..$ batch : chr "-1"
  .. .. ..$ sn    : chr "B03203E412"
  .. ..$ active_wgcna: chr "vis"
  .. ..$ vis         :List of 1
  .. .. ..$ wgcna_genes: chr [1:4058] "Gene0000040" "Gene0000050" "Gene0000070" "Gene0000080" ...
  ..@ version     :Classes 'package_version', 'numeric_version'  hidden list of 1
  .. ..$ : int [1:4] 3 1 5 9900
  ..@ commands    :List of 9
  .. ..$ NormalizeData.Spatial   :Formal class 'SeuratCommand' [package "SeuratObject"] with 5 slots
  .. .. .. ..@ name       : chr "NormalizeData.Spatial"
  .. .. .. ..@ time.stamp : POSIXct[1:1], format: "2024-03-18 12:11:13"
  .. .. .. ..@ assay.used : chr "Spatial"
  .. .. .. ..@ call.string: chr "NormalizeData(object)"
  .. .. .. ..@ params     :List of 5
  .. .. .. .. ..$ assay               : chr "Spatial"
  .. .. .. .. ..$ normalization.method: chr "LogNormalize"
  .. .. .. .. ..$ scale.factor        : num 10000
  .. .. .. .. ..$ margin              : num 1
  .. .. .. .. ..$ verbose             : logi TRUE
  .. ..$ SCTransform.Spatial     :Formal class 'SeuratCommand' [package "SeuratObject"] with 5 slots
  .. .. .. ..@ name       : chr "SCTransform.Spatial"
  .. .. .. ..@ time.stamp : POSIXct[1:1], format: "2024-04-08 19:49:28"
  .. .. .. ..@ assay.used : chr "Spatial"
  .. .. .. ..@ call.string: chr "SCTransform(tA, assay = \"Spatial\", verbose = FALSE)"
  .. .. .. ..@ params     :List of 14
  .. .. .. .. ..$ assay                  : chr "Spatial"
  .. .. .. .. ..$ new.assay.name         : chr "SCT"
  .. .. .. .. ..$ do.correct.umi         : logi TRUE
  .. .. .. .. ..$ ncells                 : num 5000
  .. .. .. .. ..$ variable.features.n    : num 3000
  .. .. .. .. ..$ variable.features.rv.th: num 1.3
  .. .. .. .. ..$ do.scale               : logi FALSE
  .. .. .. .. ..$ do.center              : logi TRUE
  .. .. .. .. ..$ clip.range             : num [1:2] -4.05 4.05
  .. .. .. .. ..$ vst.flavor             : chr "v2"
  .. .. .. .. ..$ conserve.memory        : logi FALSE
  .. .. .. .. ..$ return.only.var.genes  : logi TRUE
  .. .. .. .. ..$ seed.use               : num 1448145
  .. .. .. .. ..$ verbose                : logi FALSE
  .. ..$ NormalizeData.SCT       :Formal class 'SeuratCommand' [package "SeuratObject"] with 5 slots
  .. .. .. ..@ name       : chr "NormalizeData.SCT"
  .. .. .. ..@ time.stamp : POSIXct[1:1], format: "2024-04-08 19:57:51"
  .. .. .. ..@ assay.used : chr "SCT"
  .. .. .. ..@ call.string: chr "NormalizeData(.)"
  .. .. .. ..@ params     :List of 5
  .. .. .. .. ..$ assay               : chr "SCT"
  .. .. .. .. ..$ normalization.method: chr "LogNormalize"
  .. .. .. .. ..$ scale.factor        : num 10000
  .. .. .. .. ..$ margin              : num 1
  .. .. .. .. ..$ verbose             : logi TRUE
  .. ..$ FindVariableFeatures.SCT:Formal class 'SeuratCommand' [package "SeuratObject"] with 5 slots
  .. .. .. ..@ name       : chr "FindVariableFeatures.SCT"
  .. .. .. ..@ time.stamp : POSIXct[1:1], format: "2024-04-08 19:57:51"
  .. .. .. ..@ assay.used : chr "SCT"
  .. .. .. ..@ call.string: chr "FindVariableFeatures(.)"
  .. .. .. ..@ params     :List of 12
  .. .. .. .. ..$ assay              : chr "SCT"
  .. .. .. .. ..$ selection.method   : chr "vst"
  .. .. .. .. ..$ loess.span         : num 0.3
  .. .. .. .. ..$ clip.max           : chr "auto"
  .. .. .. .. ..$ mean.function      :function (mat, display_progress)  
  .. .. .. .. ..$ dispersion.function:function (mat, display_progress)  
  .. .. .. .. ..$ num.bin            : num 20
  .. .. .. .. ..$ binning.method     : chr "equal_width"
  .. .. .. .. ..$ nfeatures          : num 2000
  .. .. .. .. ..$ mean.cutoff        : num [1:2] 0.1 8
  .. .. .. .. ..$ dispersion.cutoff  : num [1:2] 1 Inf
  .. .. .. .. ..$ verbose            : logi TRUE
  .. ..$ ScaleData.SCT           :Formal class 'SeuratCommand' [package "SeuratObject"] with 5 slots
  .. .. .. ..@ name       : chr "ScaleData.SCT"
  .. .. .. ..@ time.stamp : POSIXct[1:1], format: "2024-04-08 19:57:51"
  .. .. .. ..@ assay.used : chr "SCT"
  .. .. .. ..@ call.string: chr "ScaleData(.)"
  .. .. .. ..@ params     :List of 10
  .. .. .. .. ..$ features          : chr [1:2000] "Gene0062990" "Gene0061940" "Gene0118390" "Gene0327200" ...
  .. .. .. .. ..$ assay             : chr "SCT"
  .. .. .. .. ..$ model.use         : chr "linear"
  .. .. .. .. ..$ use.umi           : logi FALSE
  .. .. .. .. ..$ do.scale          : logi TRUE
  .. .. .. .. ..$ do.center         : logi TRUE
  .. .. .. .. ..$ scale.max         : num 10
  .. .. .. .. ..$ block.size        : num 1000
  .. .. .. .. ..$ min.cells.to.block: num 491
  .. .. .. .. ..$ verbose           : logi TRUE
  .. ..$ RunPCA.SCT              :Formal class 'SeuratCommand' [package "SeuratObject"] with 5 slots
  .. .. .. ..@ name       : chr "RunPCA.SCT"
  .. .. .. ..@ time.stamp : POSIXct[1:1], format: "2024-04-08 19:57:52"
  .. .. .. ..@ assay.used : chr "SCT"
  .. .. .. ..@ call.string: chr "RunPCA(.)"
  .. .. .. ..@ params     :List of 10
  .. .. .. .. ..$ assay          : chr "SCT"
  .. .. .. .. ..$ npcs           : num 50
  .. .. .. .. ..$ rev.pca        : logi FALSE
  .. .. .. .. ..$ weight.by.var  : logi TRUE
  .. .. .. .. ..$ verbose        : logi TRUE
  .. .. .. .. ..$ ndims.print    : int [1:5] 1 2 3 4 5
  .. .. .. .. ..$ nfeatures.print: num 30
  .. .. .. .. ..$ reduction.name : chr "pca"
  .. .. .. .. ..$ reduction.key  : chr "PC_"
  .. .. .. .. ..$ seed.use       : num 42
  .. ..$ FindNeighbors.SCT.pca   :Formal class 'SeuratCommand' [package "SeuratObject"] with 5 slots
  .. .. .. ..@ name       : chr "FindNeighbors.SCT.pca"
  .. .. .. ..@ time.stamp : POSIXct[1:1], format: "2024-04-08 19:57:53"
  .. .. .. ..@ assay.used : chr "SCT"
  .. .. .. ..@ call.string: chr "FindNeighbors(ta_obj, dims = 1:30)"
  .. .. .. ..@ params     :List of 16
  .. .. .. .. ..$ reduction      : chr "pca"
  .. .. .. .. ..$ dims           : int [1:30] 1 2 3 4 5 6 7 8 9 10 ...
  .. .. .. .. ..$ assay          : chr "SCT"
  .. .. .. .. ..$ k.param        : num 20
  .. .. .. .. ..$ return.neighbor: logi FALSE
  .. .. .. .. ..$ compute.SNN    : logi TRUE
  .. .. .. .. ..$ prune.SNN      : num 0.0667
  .. .. .. .. ..$ nn.method      : chr "annoy"
  .. .. .. .. ..$ n.trees        : num 50
  .. .. .. .. ..$ annoy.metric   : chr "euclidean"
  .. .. .. .. ..$ nn.eps         : num 0
  .. .. .. .. ..$ verbose        : logi TRUE
  .. .. .. .. ..$ do.plot        : logi FALSE
  .. .. .. .. ..$ graph.name     : chr [1:2] "SCT_nn" "SCT_snn"
  .. .. .. .. ..$ l2.norm        : logi FALSE
  .. .. .. .. ..$ cache.index    : logi FALSE
  .. ..$ FindClusters            :Formal class 'SeuratCommand' [package "SeuratObject"] with 5 slots
  .. .. .. ..@ name       : chr "FindClusters"
  .. .. .. ..@ time.stamp : POSIXct[1:1], format: "2024-04-08 19:57:53"
  .. .. .. ..@ assay.used : chr "SCT"
  .. .. .. ..@ call.string: chr "FindClusters(ta_obj, verbose = TRUE)"
  .. .. .. ..@ params     :List of 11
  .. .. .. .. ..$ graph.name      : chr "SCT_snn"
  .. .. .. .. ..$ cluster.name    : chr "SCT_snn_res.0.8"
  .. .. .. .. ..$ modularity.fxn  : num 1
  .. .. .. .. ..$ resolution      : num 0.8
  .. .. .. .. ..$ method          : chr "matrix"
  .. .. .. .. ..$ algorithm       : num 1
  .. .. .. .. ..$ n.start         : num 10
  .. .. .. .. ..$ n.iter          : num 10
  .. .. .. .. ..$ random.seed     : num 0
  .. .. .. .. ..$ group.singletons: logi TRUE
  .. .. .. .. ..$ verbose         : logi TRUE
  .. ..$ RunUMAP.SCT.pca         :Formal class 'SeuratCommand' [package "SeuratObject"] with 5 slots
  .. .. .. ..@ name       : chr "RunUMAP.SCT.pca"
  .. .. .. ..@ time.stamp : POSIXct[1:1], format: "2024-04-08 19:57:57"
  .. .. .. ..@ assay.used : chr "SCT"
  .. .. .. ..@ call.string: chr "RunUMAP(ta_obj, dims = 1:30)"
  .. .. .. ..@ params     :List of 25
  .. .. .. .. ..$ dims                : int [1:30] 1 2 3 4 5 6 7 8 9 10 ...
  .. .. .. .. ..$ reduction           : chr "pca"
  .. .. .. .. ..$ assay               : chr "SCT"
  .. .. .. .. ..$ slot                : chr "data"
  .. .. .. .. ..$ umap.method         : chr "uwot"
  .. .. .. .. ..$ return.model        : logi FALSE
  .. .. .. .. ..$ n.neighbors         : int 30
  .. .. .. .. ..$ n.components        : int 2
  .. .. .. .. ..$ metric              : chr "cosine"
  .. .. .. .. ..$ learning.rate       : num 1
  .. .. .. .. ..$ min.dist            : num 0.3
  .. .. .. .. ..$ spread              : num 1
  .. .. .. .. ..$ set.op.mix.ratio    : num 1
  .. .. .. .. ..$ local.connectivity  : int 1
  .. .. .. .. ..$ repulsion.strength  : num 1
  .. .. .. .. ..$ negative.sample.rate: int 5
  .. .. .. .. ..$ uwot.sgd            : logi FALSE
  .. .. .. .. ..$ seed.use            : int 42
  .. .. .. .. ..$ angular.rp.forest   : logi FALSE
  .. .. .. .. ..$ densmap             : logi FALSE
  .. .. .. .. ..$ dens.lambda         : num 2
  .. .. .. .. ..$ dens.frac           : num 0.3
  .. .. .. .. ..$ dens.var.shift      : num 0.1
  .. .. .. .. ..$ verbose             : logi TRUE
  .. .. .. .. ..$ reduction.name      : chr "umap"
  ..@ tools       : Named list()

@YaoZY157
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YaoZY157 commented Jul 9, 2024

I have the same problem. Did solve the problem? @liuxiawei

@liuxiawei
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I have the same problem. Did solve the problem? @liuxiawei

No

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@liuxiawei @smorabit @YaoZY157