AustinHartman
commented
2 years ago Hi, I am actually able to load in liver 1 slice 1. The warning suggests a lot of missing data - could you double check all of the cell boundary files are present? By my count there are 1,791 of them.
I am trying to analyze some of Vizgen's public MERFISH/MERSCOPE data, but am encountering the following error: "Error in UseMethod(generic = "CreateSegmentation", object = coords) : no applicable method for 'CreateSegmentation' applied to an object of class "NULL" See below for additional information on system, session and commands.
The folder structure I use matches the one in the vigniette and in their mouse brain data release 1:1. This does not seem to be an issue with my system, since the mouse brain data from the vigniette can be imported and analyzed just fine. All other datasets they made available (mouse lung and human cancer samples) do not work though. There don't seem to be changes to the files they provide in these releases vs brain and I have had the same error on three systems running Windows 10, Windows 10 Pro and Windows 11 Pro with different R versions and 32-256 GB of memory.
This is the data I am trying to use, but the same can be said for any other MERFISH/MERSCOPE release that is not mouse brain (mouse liver L1S1: https://console.cloud.google.com/storage/browser/vz-liver-showcase/Liver1Slice1;tab=objects?pageState=(%22StorageObjectListTable%22:(%22f%22:%22%255B%255D%22))&prefix=&forceOnObjectsSortingFiltering=false&pli=1
session info for one of the systems I used
Matrix products: default
locale: [1] LC_COLLATE=German_Germany.1252 LC_CTYPE=German_Germany.1252 LC_MONETARY=German_Germany.1252 [4] LC_NUMERIC=C LC_TIME=German_Germany.1252
attached base packages: [1] stats graphics grDevices utils datasets methods base
other attached packages: [1] hdf5r_1.3.5 future_1.27.0 dplyr_1.0.9 sp_1.5-0 SeuratObject_4.1.0 [6] Seurat_4.1.0.9007 remotes_2.4.2
loaded via a namespace (and not attached): [1] nlme_3.1-153 spatstat.sparse_2.1-1 matrixStats_0.62.0 bit64_4.0.5
[5] RcppAnnoy_0.0.19 RColorBrewer_1.1-3 httr_1.4.3 sctransform_0.3.3
[9] tools_4.1.2 utf8_1.2.2 R6_2.5.1 irlba_2.3.5
[13] rpart_4.1-15 KernSmooth_2.23-20 uwot_0.1.11 mgcv_1.8-38
[17] rgeos_0.5-9 lazyeval_0.2.2 colorspace_2.0-3 tidyselect_1.1.2
[21] gridExtra_2.3 bit_4.0.4 curl_4.3.2 compiler_4.1.2
[25] progressr_0.10.1 cli_3.3.0 plotly_4.10.0 scales_1.2.0
[29] lmtest_0.9-40 spatstat.data_2.2-0 ggridges_0.5.3 pbapply_1.5-0
[33] goftest_1.2-3 stringr_1.4.0 digest_0.6.29 spatstat.utils_2.3-1 [37] pkgconfig_2.0.3 htmltools_0.5.3 parallelly_1.32.1 fastmap_1.1.0
[41] htmlwidgets_1.5.4 rlang_1.0.4 shiny_1.7.2 generics_0.1.3
[45] zoo_1.8-10 jsonlite_1.8.0 spatstat.random_2.2-0 ica_1.0-3
[49] magrittr_2.0.3 patchwork_1.1.1 Matrix_1.3-4 Rcpp_1.0.9
[53] munsell_0.5.0 fansi_1.0.3 abind_1.4-5 reticulate_1.25
[57] lifecycle_1.0.1 stringi_1.7.8 MASS_7.3-54 Rtsne_0.16
[61] plyr_1.8.7 grid_4.1.2 parallel_4.1.2 listenv_0.8.0
[65] promises_1.2.0.1 ggrepel_0.9.1 deldir_1.0-6 miniUI_0.1.1.1
[69] lattice_0.20-45 cowplot_1.1.1 splines_4.1.2 tensor_1.5
[73] pillar_1.8.0 igraph_1.3.4 spatstat.geom_2.4-0 future.apply_1.9.0
[77] reshape2_1.4.4 codetools_0.2-18 leiden_0.4.2 glue_1.6.2
[81] data.table_1.14.2 png_0.1-7 vctrs_0.4.1 httpuv_1.6.5
[85] polyclip_1.10-0 gtable_0.3.0 RANN_2.6.1 purrr_0.3.4
[89] spatstat.core_2.4-4 tidyr_1.2.0 scattermore_0.8 ggplot2_3.3.6
[93] mime_0.12 xtable_1.8-4 later_1.3.0 survival_3.2-13
[97] viridisLite_0.4.0 tibble_3.1.8 cluster_2.1.2 globals_0.15.1
[101] fitdistrplus_1.1-8 ellipsis_0.3.2 ROCR_1.0-11
This is what I tried to do - copied pretty much 1:1 from the tutorial: