Error Converting Seurat to SingleCellExperiment Object #4639
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Hi, Could you give some information on your object. Number of assays, nrows,ncols etc.? |
torkencz
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From what I am seeing this is a returning issue. #4633. Will take a look. This should be a temporary fix. |
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@torkencz Thank you so much for providing the temporary fix. It worked. |
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I am experiencing the same issue - possibly a bug with the new update? Thanks for the work around code, will use that for now. |
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Hi can someone share an object (or a subsampled / dummy version that reproduces the issue) with us at seuratpackage@gmail.com so we can fix this issue? |
torkencz
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I found what was happening. In the in line 1187 in as.SingleCellExperiment |
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This issue has been automatically closed because there has been no response to our request for more information from the original author. With only the information that is currently in the issue, we don't have enough information to take action. Please reach out if you have or find the answers we need so that we can investigate further. |
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Hi all, This bug should be resolved now on the |
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Hello, I've tried the DietSeurat suggestions and the newest "develop" branch and am still facing the issues described above.
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I am using Seurat v4 and trying to convert a Seurat object 'Abc' to SingleCellExperiment Object using the code below.
Abc_SCE <- as.SingleCellExperiment(Abc)This is returning me an error message as below :
Error in method(object) : all assays must have the same nrow and ncol
Packages in use:
Seurat v4.0.3
Seurat Object v4.0.2
Single Cell Experiment v1.14.1
sessionInfo()R>sessionInfo()
R version 4.1.0 (2021-05-18)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19042)
Matrix products: default
locale:
[1] LC_COLLATE=English_India.1252 LC_CTYPE=English_India.1252 LC_MONETARY=English_India.1252 LC_NUMERIC=C
[5] LC_TIME=English_India.1252
attached base packages:
[1] parallel stats4 stats graphics grDevices utils datasets methods base
other attached packages:
[1] forcats_0.5.1 stringr_1.4.0 purrr_0.3.4 tidyverse_1.3.1
[5] tibble_3.1.2 pheatmap_1.0.12 readr_1.4.0 EnhancedVolcano_1.10.0
[9] ggrepel_0.9.1 MAST_1.18.0 harmony_0.1.0 Rcpp_1.0.6
[13] tidyr_1.1.3 scCATCH_2.1 ggforce_0.3.3 patchwork_1.1.1
[17] scater_1.20.0 scuttle_1.2.0 SingleCellExperiment_1.14.1 SummarizedExperiment_1.22.0
[21] Biobase_2.52.0 GenomicRanges_1.44.0 GenomeInfoDb_1.28.0 IRanges_2.26.0
[25] S4Vectors_0.30.0 BiocGenerics_0.38.0 MatrixGenerics_1.4.0 matrixStats_0.59.0
[29] cowplot_1.1.1 ggpubr_0.4.0 magrittr_2.0.1 clustree_0.4.3
[33] ggraph_2.0.5 dplyr_1.0.6 ggplot2_3.3.4 SeuratObject_4.0.2
[37] Seurat_4.0.3 devtools_2.4.2 usethis_2.0.1 RColorBrewer_1.1-2
[41] installr_0.23.2
loaded via a namespace (and not attached):
[1] rappdirs_0.3.3 rtracklayer_1.52.0 scattermore_0.7 ragg_1.1.3 bit64_4.0.5
[6] irlba_2.3.3 DelayedArray_0.18.0 data.table_1.14.0 rpart_4.1-15 KEGGREST_1.32.0
[11] RCurl_1.98-1.3 AnnotationFilter_1.16.0 generics_0.1.0 GenomicFeatures_1.44.0 ScaledMatrix_1.0.0
[16] callr_3.7.0 RSQLite_2.2.7 RANN_2.6.1 future_1.21.0 bit_4.0.4
[21] lubridate_1.7.10 spatstat.data_2.1-0 xml2_1.3.2 httpuv_1.6.1 assertthat_0.2.1
[26] viridis_0.6.1 xfun_0.24 hms_1.1.0 promises_1.2.0.1 fansi_0.5.0
[31] restfulr_0.0.13 progress_1.2.2 dbplyr_2.1.1 readxl_1.3.1 igraph_1.2.6
[36] DBI_1.1.1 htmlwidgets_1.5.3 spatstat.geom_2.2-0 ellipsis_0.3.2 backports_1.2.1
[41] biomaRt_2.48.1 deldir_0.2-10 sparseMatrixStats_1.4.0 vctrs_0.3.8 remotes_2.4.0
[46] ensembldb_2.16.0 ROCR_1.0-11 abind_1.4-5 cachem_1.0.5 withr_2.4.2
[51] sctransform_0.3.2 GenomicAlignments_1.28.0 prettyunits_1.1.1 goftest_1.2-2 cluster_2.1.2
[56] lazyeval_0.2.2 crayon_1.4.1 labeling_0.4.2 pkgconfig_2.0.3 tweenr_1.0.2
[61] nlme_3.1-152 vipor_0.4.5 pkgload_1.2.1 ProtGenerics_1.24.0 rlang_0.4.11
[66] globals_0.14.0 lifecycle_1.0.0 miniUI_0.1.1.1 filelock_1.0.2 extrafontdb_1.0
[71] BiocFileCache_2.0.0 modelr_0.1.8 rsvd_1.0.5 ggrastr_0.2.3 cellranger_1.1.0
[76] rprojroot_2.0.2 polyclip_1.10-0 lmtest_0.9-38 Matrix_1.3-4 carData_3.0-4
[81] zoo_1.8-9 reprex_2.0.0 beeswarm_0.4.0 ggridges_0.5.3 processx_3.5.2
[86] png_0.1-7 viridisLite_0.4.0 rjson_0.2.20 bitops_1.0-7 KernSmooth_2.23-20
[91] Biostrings_2.60.0 blob_1.2.1 DelayedMatrixStats_1.14.0 parallelly_1.26.0 rstatix_0.7.0
[96] ggsignif_0.6.2 beachmat_2.8.0 scales_1.1.1 memoise_2.0.0 plyr_1.8.6
[101] ica_1.0-2 zlibbioc_1.38.0 compiler_4.1.0 tinytex_0.32 BiocIO_1.2.0
[106] ash_1.0-15 fitdistrplus_1.1-5 Rsamtools_2.8.0 cli_2.5.0 XVector_0.32.0
[111] listenv_0.8.0 pbapply_1.4-3 ps_1.6.0 MASS_7.3-54 mgcv_1.8-36
[116] tidyselect_1.1.1 stringi_1.6.2 textshaping_0.3.5 proj4_1.0-10.1 yaml_2.2.1
[121] BiocSingular_1.8.0 grid_4.1.0 tools_4.1.0 future.apply_1.7.0 rio_0.5.26
[126] rstudioapi_0.13 foreign_0.8-81 gridExtra_2.3 farver_2.1.0 Rtsne_0.15
[131] BiocManager_1.30.16 digest_0.6.27 shiny_1.6.0 car_3.0-10 broom_0.7.7
[136] ggalt_0.4.0 later_1.2.0 RcppAnnoy_0.0.18 httr_1.4.2 AnnotationDbi_1.54.1
[141] colorspace_2.0-1 rvest_1.0.0 XML_3.99-0.6 fs_1.5.0 tensor_1.5
[146] reticulate_1.20 splines_4.1.0 uwot_0.1.10 spatstat.utils_2.2-0 graphlayouts_0.7.1
[151] systemfonts_1.0.2 plotly_4.9.4 sessioninfo_1.1.1 xtable_1.8-4 jsonlite_1.7.2
[156] tidygraph_1.2.0 testthat_3.0.2 R6_2.5.0 pillar_1.6.1 htmltools_0.5.1.1
[161] mime_0.10 glue_1.4.2 fastmap_1.1.0 BiocParallel_1.26.0 BiocNeighbors_1.10.0
[166] codetools_0.2-18 maps_3.3.0 pkgbuild_1.2.0 utf8_1.2.1 lattice_0.20-44
[171] spatstat.sparse_2.0-0 curl_4.3.1 ggbeeswarm_0.6.0 leiden_0.3.8 Rttf2pt1_1.3.8
[176] zip_2.2.0 openxlsx_4.2.4 survival_3.2-11 desc_1.3.0 munsell_0.5.0
[181] GenomeInfoDbData_1.2.6 haven_2.4.1 reshape2_1.4.4 gtable_0.3.0 extrafont_0.17
[186] spatstat.core_2.1-2
PS - I am a completely new user on Github and this is my first post, so any feedback would be appreciated.
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