Error in as(counts(sce), "CsparseMatrix")
akhst7 opened this issue · comments
Describe the bug
I run a following and got an error;
dblets<-scDblFinder(sce)
Error in as(counts(sce), "CsparseMatrix") :
no method or default for coercing "Assay" to "CsparseMatrix"
MRE -- Minimal example to reproduce the bug
A sce obj was created from 10x's data set (https://www.10xgenomics.com/resources/datasets/pbmc-from-a-healthy-donor-granulocytes-removed-through-cell-sorting-3-k-1-standard-2-0-0).
A filtered bc matrix was fed into Seurat ("4.9.9.9058") to create a Seurat obj and count data was used to create the following sce obj;
count<-GetAssay(pbmc3ksorted.arc202, assay = "RNA")
sce<-SingleCellExperiment(list(counts=RNA))
> sce
class: SingleCellExperiment
dim: 36601 2707
metadata(0):
assays(1): counts
rownames(36601): MIR1302-2HG FAM138A ... AC007325.4 AC007325.2
rowData names(0):
colnames(2707): AAACAGCCAAATATCC-1 AAACAGCCAGGAACTG-1 ... TTTGTGTTCCGTGACA-1 TTTGTTGGTAGGTTTG-1
colData names(0):
reducedDimNames(0):
mainExpName: NULL
altExpNames(0):
Traceback
traceback()
4: stop(gettextf("no method or default for coercing %s to %s", dQuote(thisClass),
dQuote(Class)), domain = NA)
3: as(counts(sce), "CsparseMatrix")
2: .checkSCE(sce)
1: scDblFinder(sce)
Session info
> package.version('scDBlFinder')
[1] "1.14.0"
> sessionInfo()
R version 4.3.1 (2023-06-16)
Platform: aarch64-apple-darwin20 (64-bit)
Running under: macOS Ventura 13.5
Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/lib/libRlapack.dylib; LAPACK version 3.11.0
Random number generation:
RNG: L'Ecuyer-CMRG
Normal: Inversion
Sample: Rejection
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
time zone: America/Indiana/Indianapolis
tzcode source: internal
attached base packages:
[1] stats4 stats graphics grDevices utils datasets methods base
other attached packages:
[1] BiocParallel_1.34.2 TENxIO_1.2.0 scDblFinder_1.14.0 SingleCellExperiment_1.22.0 SummarizedExperiment_1.30.2
[6] MatrixGenerics_1.12.3 matrixStats_1.0.0 Seurat_4.9.9.9058 data.table_1.14.9 Signac_1.10.0
[11] ensembldb_2.24.0 AnnotationFilter_1.24.0 GenomicFeatures_1.52.1 AnnotationDbi_1.62.2 Biobase_2.60.0
[16] SeuratObject_4.9.9.9091 sp_2.0-0 GenomicRanges_1.52.0 GenomeInfoDb_1.36.1 IRanges_2.34.1
[21] S4Vectors_0.38.1 AnnotationHub_3.8.0 BiocFileCache_2.8.0 dbplyr_2.3.3 BiocGenerics_0.46.0
[26] future_1.33.0 magrittr_2.0.3.9000
loaded via a namespace (and not attached):
[1] ProtGenerics_1.32.0 spatstat.sparse_3.0-2 bitops_1.0-7 httr_1.4.6 RColorBrewer_1.1-3
[6] tools_4.3.1 sctransform_0.3.5 utf8_1.2.3 R6_2.5.1 lazyeval_0.2.2
[11] uwot_0.1.16 prettyunits_1.1.1 gridExtra_2.3 drcData_1.1-3 progressr_0.14.0
[16] cli_3.6.1 spatstat.explore_3.2-1 fastDummies_1.7.3 sandwich_3.0-2 mvtnorm_1.2-2
[21] spatstat.data_3.0-1 readr_2.1.4 ggridges_0.5.4 pbapply_1.7-2 Rsamtools_2.16.0
[26] scater_1.28.0 parallelly_1.36.0 plotrix_3.8-2 limma_3.56.2 rstudioapi_0.15.0
[31] RSQLite_2.3.1 generics_0.1.3 BiocIO_1.10.0 gtools_3.9.4 ica_1.0-3
[36] spatstat.random_3.1-5 car_3.1-2 dplyr_1.1.2 Matrix_1.6-1 ggbeeswarm_0.7.2
[41] fansi_1.0.4 abind_1.4-5 lifecycle_1.0.3 multcomp_1.4-25 yaml_2.3.7
[46] edgeR_3.42.4 carData_3.0-5 Rtsne_0.16 grid_4.3.1 blob_1.2.4
[51] promises_1.2.1 dqrng_0.3.0 crayon_1.5.2 miniUI_0.1.1.1 lattice_0.21-8
[56] beachmat_2.16.0 cowplot_1.1.1 KEGGREST_1.40.0 pillar_1.9.0 metapod_1.8.0
[61] rjson_0.2.21 xgboost_1.7.5.1 future.apply_1.11.0 codetools_0.2-19 fastmatch_1.1-3
[66] leiden_0.4.3 glue_1.6.2 remotes_2.4.2.1 vctrs_0.6.3 png_0.1-8
[71] spam_2.9-1 gtable_0.3.3 cachem_1.0.8 S4Arrays_1.0.5 mime_0.12
[76] survival_3.5-7 RcppRoll_0.3.0 statmod_1.5.0 bluster_1.10.0 TH.data_1.1-2
[81] interactiveDisplayBase_1.38.0 ellipsis_0.3.2 fitdistrplus_1.1-11 ROCR_1.0-11 nlme_3.1-163
[86] bit64_4.0.5 progress_1.2.2 filelock_1.0.2 RcppAnnoy_0.0.21 job_0.3.0
[91] irlba_2.3.5.1 vipor_0.4.5 KernSmooth_2.23-22 colorspace_2.1-0 DBI_1.1.3
[96] tidyselect_1.2.0 bit_4.0.5 compiler_4.3.1 curl_5.0.2 BiocNeighbors_1.18.0
[101] xml2_1.3.5 DelayedArray_0.26.7 plotly_4.10.2 rtracklayer_1.60.0 scales_1.2.1
[106] lmtest_0.9-40 rappdirs_0.3.3 stringr_1.5.0 digest_0.6.33 goftest_1.2-3
[111] spatstat.utils_3.0-3 XVector_0.40.0 htmltools_0.5.6 pkgconfig_2.0.3 sparseMatrixStats_1.12.2
[116] fastmap_1.1.1 rlang_1.1.1 htmlwidgets_1.6.2 shiny_1.7.5 DelayedMatrixStats_1.22.5
[121] zoo_1.8-12 jsonlite_1.8.7 BiocSingular_1.16.0 RCurl_1.98-1.12 scuttle_1.10.2
[126] GenomeInfoDbData_1.2.10 dotCall64_1.0-2 sceasy_0.0.7 patchwork_1.1.3 munsell_0.5.0
[131] Rcpp_1.0.11 viridis_0.6.4 reticulate_1.31 stringi_1.7.12 zlibbioc_1.46.0
[136] MASS_7.3-60 plyr_1.8.8 parallel_4.3.1 listenv_0.9.0 ggrepel_0.9.3
[141] deldir_1.0-9 Biostrings_2.68.1 splines_4.3.1 tensor_1.5 hms_1.1.3
[146] locfit_1.5-9.8 igraph_1.5.1 spatstat.geom_3.2-4 RcppHNSW_0.4.1 reshape2_1.4.4
[151] biomaRt_2.56.1 ScaledMatrix_1.8.1 BiocVersion_3.17.1 XML_3.99-0.14 drc_3.2-0
[156] scran_1.28.2 BiocManager_1.30.22 tzdb_0.4.0 httpuv_1.6.11 RANN_2.6.1
[161] tidyr_1.3.0 purrr_1.0.2 polyclip_1.10-4 scattermore_1.2 ggplot2_3.4.3
[166] BiocBaseUtils_1.2.0 rsvd_1.0.5 xtable_1.8-4 restfulr_0.0.15 RSpectra_0.16-1
[171] later_1.3.1 viridisLite_0.4.2 tibble_3.2.1 memoise_2.0.1 beeswarm_0.4.0
[176] GenomicAlignments_1.36.0 cluster_2.1.4 globals_0.16.2
Hi,
your code is wrong.
You're extracting the assay as count but aren't passing that to SingleCellExperiment(). Even if you were using it, that's a Seurat object and the SCE won't be working with anything downstream. Extract your assay with GetAssayData instead.