Coercion from SCE drops off rowData

[TuomasBorman]

When SingleCellExperiment is converted into SummarizedExperiment, the resulting SE does not include rowData that was in the input,

library(SingleCellExperiment)

# Create dummy data
n_cells <- 100
n_genes <- 50

# Create a dummy SingleCellExperiment object
sce <- SingleCellExperiment(
    assays = list(counts = matrix(rpois(n_cells * n_genes, lambda = 10), nrow = n_genes, ncol = n_cells)),
    colData = DataFrame(
        cell_id = paste0("cell", 1:n_cells),
        condition = sample(c("control", "treatment"), n_cells, replace = TRUE)
    ),
    rowData = DataFrame(
        gene_id = paste0("gene", 1:n_genes),
        gene_name = paste0("Gene_", 1:n_genes)
    )
)

se <- as(sce, "SummarizedExperiment")

# Show rowData
rowData(sce) |> head()
rowData(se) |> head()

Session info

R Under development (unstable) (2024-01-12 r85803)
Platform: x86_64-pc-linux-gnu
Running under: Linux Mint 21

Matrix products: default
BLAS: /opt/R/devel/lib/R/lib/libRblas.so
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.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
[5] LC_MONETARY=fi_FI.UTF-8 LC_MESSAGES=en_US.UTF-8 LC_PAPER=fi_FI.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=fi_FI.UTF-8 LC_IDENTIFICATION=C

time zone: Europe/Helsinki
tzcode source: system (glibc)

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

other attached packages:
[1] TreeSummarizedExperiment_2.13.0 Biostrings_2.73.1 XVector_0.45.0 SingleCellExperiment_1.27.2
[5] SummarizedExperiment_1.35.1 Biobase_2.64.0 GenomicRanges_1.57.1 GenomeInfoDb_1.41.1
[9] IRanges_2.39.1 S4Vectors_0.43.1 BiocGenerics_0.51.0 MatrixGenerics_1.17.0
[13] matrixStats_1.3.0

loaded via a namespace (and not attached):
[1] DBI_1.2.3 bitops_1.0-7 remotes_2.5.0 biomaRt_2.59.0 rlang_1.1.4
[6] magrittr_2.0.3 compiler_4.4.0 RSQLite_2.3.7 GenomicFeatures_1.55.1 png_0.1-8
[11] vctrs_0.6.5 stringr_1.5.1 profvis_0.3.8 pkgconfig_2.0.3 crayon_1.5.3
[16] fastmap_1.2.0 dbplyr_2.5.0 ellipsis_0.3.2 utf8_1.2.4 Rsamtools_2.19.2
[21] promises_1.3.0 sessioninfo_1.2.2 UCSC.utils_1.1.0 purrr_1.0.2 bit_4.0.5
[26] zlibbioc_1.51.1 cachem_1.1.0 jsonlite_1.8.8 progress_1.2.3 blob_1.2.4
[31] later_1.3.2 DelayedArray_0.31.8 BiocParallel_1.39.0 parallel_4.4.0 prettyunits_1.2.0
[36] R6_2.5.1 stringi_1.8.4 rtracklayer_1.63.0 pkgload_1.3.3 Rcpp_1.0.13
[41] usethis_2.2.2 httpuv_1.6.15 Matrix_1.6-5 tidyselect_1.2.1 yaml_2.3.9
[46] rstudioapi_0.16.0 abind_1.4-5 codetools_0.2-19 miniUI_0.1.1.1 curl_5.2.1
[51] pkgbuild_1.4.3 lattice_0.22-6 tibble_3.2.1 shiny_1.8.0 treeio_1.29.0
[56] withr_3.0.0 KEGGREST_1.45.1 desc_1.4.3 urlchecker_1.0.1 BiocFileCache_2.11.1
[61] xml2_1.3.6 pillar_1.9.0 filelock_1.0.3 generics_0.1.3 rprojroot_2.0.4
[66] RCurl_1.98-1.14 hms_1.1.3 tidytree_0.4.6 xtable_1.8-4 glue_1.7.0
[71] lazyeval_0.2.2 tools_4.4.0 BiocIO_1.14.0 GenomicAlignments_1.39.1 annotate_1.81.1
[76] fs_1.6.4 XML_3.99-0.16.1 grid_4.4.0 tidyr_1.3.1 ape_5.8
[81] devtools_2.4.5 AnnotationDbi_1.67.0 nlme_3.1-165 GenomeInfoDbData_1.2.12 restfulr_0.0.15
[86] cli_3.6.3 rappdirs_0.3.3 fansi_1.0.6 S4Arrays_1.5.4 dplyr_1.1.4
[91] yulab.utils_0.1.4 digest_0.6.36 SparseArray_1.5.21 rjson_0.2.21 htmlwidgets_1.6.4
[96] memoise_2.0.1 htmltools_0.5.8.1 lifecycle_1.0.4 httr_1.4.7 mime_0.12
[101] bit64_4.0.5

[PeteHaitch]

That is a bit annoying.
Until @hpages can chime in, I'll just note that stepping through the coercion as SingleCellExperiment -> RangedSummarizedExperiment -> SummarizedExperiment does seem to work:

suppressPackageStartupMessages(library(SingleCellExperiment))

# Create dummy data
n_cells <- 100
n_genes <- 50

# Create a dummy SingleCellExperiment object
sce <- SingleCellExperiment(
  assays = list(counts = matrix(rpois(n_cells * n_genes, lambda = 10), nrow = n_genes, ncol = n_cells)),
  colData = DataFrame(
    cell_id = paste0("cell", 1:n_cells),
    condition = sample(c("control", "treatment"), n_cells, replace = TRUE)
  ),
  rowData = DataFrame(
    gene_id = paste0("gene", 1:n_genes),
    gene_name = paste0("Gene_", 1:n_genes)
  )
)

# rowData not propagated
rowData(as(sce, "SummarizedExperiment"))
#> DataFrame with 50 rows and 0 columns

# rowData propagated
rowData(as(as(sce, "RangedSummarizedExperiment"), "SummarizedExperiment"))
#> DataFrame with 50 rows and 2 columns
#>         gene_id   gene_name
#>     <character> <character>
#> 1         gene1      Gene_1
#> 2         gene2      Gene_2
#> 3         gene3      Gene_3
#> 4         gene4      Gene_4
#> 5         gene5      Gene_5
#> ...         ...         ...
#> 46       gene46     Gene_46
#> 47       gene47     Gene_47
#> 48       gene48     Gene_48
#> 49       gene49     Gene_49
#> 50       gene50     Gene_50

I think it may be due to how SingleCellExperiment is defined resulting in it being 2 steps away from SummarizedExperiment

showClass('SingleCellExperiment')
#> Class "SingleCellExperiment" [package "SingleCellExperiment"]
#> 
#> Slots:
#>                                                                 
#> Name:           int_elementMetadata                  int_colData
#> Class:                    DataFrame                    DataFrame
#>                                                                 
#> Name:                  int_metadata                    rowRanges
#> Class:                         list GenomicRanges_OR_GRangesList
#>                                                                 
#> Name:                       colData                       assays
#> Class:                    DataFrame               Assays_OR_NULL
#>                                                                 
#> Name:                         NAMES              elementMetadata
#> Class:            character_OR_NULL                    DataFrame
#>                                    
#> Name:                      metadata
#> Class:                         list
#> 
#> Extends: 
#> Class "RangedSummarizedExperiment", directly
#> Class "SummarizedExperiment", by class "RangedSummarizedExperiment", distance 2
#> Class "RectangularData", by class "RangedSummarizedExperiment", distance 3
#> Class "Vector", by class "RangedSummarizedExperiment", distance 3
#> Class "Annotated", by class "RangedSummarizedExperiment", distance 4
#> Class "vector_OR_Vector", by class "RangedSummarizedExperiment", distance 4

Session info

sessioninfo::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
#>  setting  value
#>  version  R version 4.4.1 (2024-06-14)
#>  os       macOS Sonoma 14.5
#>  system   aarch64, darwin20
#>  ui       X11
#>  language (EN)
#>  collate  en_US.UTF-8
#>  ctype    en_US.UTF-8
#>  tz       Australia/Melbourne
#>  date     2024-07-31
#>  pandoc   3.2 @ /usr/local/bin/ (via rmarkdown)
#> 
#> ─ Packages ───────────────────────────────────────────────────────────────────
#>  package              * version date (UTC) lib source
#>  abind                  1.4-5   2016-07-21 [1] CRAN (R 4.4.0)
#>  Biobase              * 2.65.0  2024-05-04 [1] Bioconductor 3.20 (R 4.4.0)
#>  BiocGenerics         * 0.51.0  2024-05-04 [1] Bioconductor 3.20 (R 4.4.0)
#>  cli                    3.6.3   2024-06-21 [1] CRAN (R 4.4.0)
#>  crayon                 1.5.3   2024-06-20 [1] CRAN (R 4.4.0)
#>  DelayedArray           0.31.10 2024-07-28 [1] Bioconductor 3.20 (R 4.4.1)
#>  digest                 0.6.36  2024-06-23 [1] CRAN (R 4.4.0)
#>  evaluate               0.24.0  2024-06-10 [1] CRAN (R 4.4.0)
#>  fastmap                1.2.0   2024-05-15 [1] CRAN (R 4.4.0)
#>  fs                     1.6.4   2024-04-25 [1] CRAN (R 4.4.0)
#>  GenomeInfoDb         * 1.41.1  2024-05-24 [1] Bioconductor 3.20 (R 4.4.0)
#>  GenomeInfoDbData       1.2.12  2024-03-28 [1] Bioconductor
#>  GenomicRanges        * 1.57.1  2024-06-12 [1] Bioconductor 3.20 (R 4.4.1)
#>  glue                   1.7.0   2024-01-09 [1] CRAN (R 4.4.0)
#>  htmltools              0.5.8.1 2024-04-04 [1] CRAN (R 4.4.0)
#>  httr                   1.4.7   2023-08-15 [1] CRAN (R 4.4.0)
#>  IRanges              * 2.39.2  2024-07-17 [1] Bioconductor 3.20 (R 4.4.1)
#>  jsonlite               1.8.8   2023-12-04 [1] CRAN (R 4.4.0)
#>  knitr                  1.48    2024-07-07 [1] CRAN (R 4.4.0)
#>  lattice                0.22-6  2024-03-20 [1] CRAN (R 4.4.1)
#>  lifecycle              1.0.4   2023-11-07 [1] CRAN (R 4.4.0)
#>  Matrix                 1.7-0   2024-04-26 [1] CRAN (R 4.4.1)
#>  MatrixGenerics       * 1.17.0  2024-05-04 [1] Bioconductor 3.20 (R 4.4.0)
#>  matrixStats          * 1.3.0   2024-04-11 [1] CRAN (R 4.4.0)
#>  R6                     2.5.1   2021-08-19 [1] CRAN (R 4.4.0)
#>  reprex                 2.1.1   2024-07-06 [1] CRAN (R 4.4.0)
#>  rlang                  1.1.4   2024-06-04 [1] CRAN (R 4.4.0)
#>  rmarkdown              2.27    2024-05-17 [1] CRAN (R 4.4.0)
#>  rstudioapi             0.16.0  2024-03-24 [1] CRAN (R 4.4.0)
#>  S4Arrays               1.5.5   2024-07-21 [1] Bioconductor 3.20 (R 4.4.1)
#>  S4Vectors            * 0.43.2  2024-07-17 [1] Bioconductor 3.20 (R 4.4.1)
#>  sessioninfo            1.2.2   2021-12-06 [1] CRAN (R 4.4.0)
#>  SingleCellExperiment * 1.27.2  2024-05-24 [1] Bioconductor 3.20 (R 4.4.0)
#>  SparseArray            1.5.27  2024-07-29 [1] Bioconductor 3.20 (R 4.4.1)
#>  SummarizedExperiment * 1.35.1  2024-06-28 [1] Bioconductor 3.20 (R 4.4.1)
#>  UCSC.utils             1.1.0   2024-05-04 [1] Bioconductor 3.20 (R 4.4.0)
#>  withr                  3.0.0   2024-01-16 [1] CRAN (R 4.4.0)
#>  xfun                   0.46    2024-07-18 [1] CRAN (R 4.4.0)
#>  XVector                0.45.0  2024-05-04 [1] Bioconductor 3.20 (R 4.4.0)
#>  yaml                   2.3.10  2024-07-26 [1] CRAN (R 4.4.0)
#>  zlibbioc               1.51.1  2024-06-05 [1] Bioconductor 3.20 (R 4.4.0)
#> 
#>  [1] /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/library
#> 
#> ──────────────────────────────────────────────────────────────────────────────

[ChangqingW]

Not sure if this is relevant, but using rowRanges()<- on a SCE also removes the rowData

library(SingleCellExperiment)

# Create dummy data
n_cells <- 100
n_genes <- 50

# Create a dummy SingleCellExperiment object
sce <- SingleCellExperiment(
    assays = list(counts = matrix(rpois(n_cells * n_genes, lambda = 10), nrow = n_genes, ncol = n_cells)),
    colData = DataFrame(
        cell_id = paste0("cell", 1:n_cells),
        condition = sample(c("control", "treatment"), n_cells, replace = TRUE)
    ),
    rowData = DataFrame(
        gene_id = paste0("gene", 1:n_genes),
        gene_name = paste0("Gene_", 1:n_genes)
    )
)

rowData(sce) |> head()
rowRanges(sce)<-do.call(GRangesList, lapply(1:n_genes, \(x) GRanges()))
rowData(sce) |> head()

I also noticed when using rowRanges(sce)[]<-, rowData becomes NAs instead.

rowRanges(sce)[seq_len(n_genes)]<-do.call(GRangesList, lapply(1:n_genes, \(x) GRanges()))

[PeteHaitch]

@hpages giving this a nudge in the hope you have time to clarify the issue and if it can be 'fixed'.