Image filp？

[FelixZ95]

A great job! I met some problems when I used SPATA3.1.0. The image will not be the same as the original; could you please help me solve this problem? thanks Code: object <- initiateSpataObjectVisium(sample_name = N, directory_visium = xxx) plotImage(object)

Origian picture:

SessionInfo: R version 4.4.0 (2024-04-24) Platform: x86_64-pc-linux-gnu Running under: Ubuntu 22.04.4 LTS

Matrix products: default BLAS/LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.so; LAPACK version 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=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C

time zone: Asia/Shanghai tzcode source: system (glibc)

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

other attached packages: [1] SPATA2_3.1.0 lubridate_1.9.3 forcats_1.0.0 stringr_1.5.1 readr_2.1.5 tidyr_1.3.0
[7] tibble_3.2.1 ggplot2_3.5.1 tidyverse_2.0.0 purrr_1.0.2 dplyr_1.1.4 shiny_1.9.1
[13] SeuratObject_4.1.4 Seurat_4.4.0

loaded via a namespace (and not attached): [1] reactable_0.4.4 fs_1.6.4 matrixStats_1.4.0 spatstat.sparse_3.1-0
[5] bitops_1.0-8 sf_1.0-17 shinybusy_0.3.3 fontawesome_0.5.2
[9] devtools_2.4.5 EBImage_4.46.0 httr_1.4.7 RColorBrewer_1.1-3
[13] doParallel_1.0.17 profvis_0.3.8 tools_4.4.0 sctransform_0.4.1
[17] backports_1.5.0 utf8_1.2.4 R6_2.5.1 mgcv_1.9-1
[21] lazyeval_0.2.2 uwot_0.2.2 anndata_0.7.5.6 GetoptLong_1.0.5
[25] urlchecker_1.0.1 withr_3.0.1 sp_2.1-4 prettyunits_1.2.0
[29] gridExtra_2.3 SeuratWrappers_0.3.1 progressr_0.14.0 textshaping_0.4.0
[33] cli_3.6.3 Biobase_2.64.0 pacman_0.5.1 spatstat.explore_3.3-2
[37] isoband_0.2.7 sass_0.4.9 labeling_0.4.3 spatstat.data_3.1-2
[41] proxy_0.4-27 ggridges_0.5.6 pbapply_1.7-2 systemfonts_1.1.0
[45] SPATAData_0.0.0.9000 dbscan_1.2-0 svglite_2.1.2 R.utils_2.12.2
[49] stringdist_0.9.12 shinyhelper_0.3.2.9000 parallelly_1.38.0 sessioninfo_1.2.2
[53] rstudioapi_0.16.0 FNN_1.1.4 visNetwork_2.1.2 generics_0.1.3
[57] shape_1.4.6.1 ica_1.0-3 spatstat.random_3.3-1 vroom_1.6.5
[61] zip_2.3.0 car_3.1-2 Matrix_1.6-1.1 fansi_1.0.6
[65] S4Vectors_0.42.1 abind_1.4-5 R.methodsS3_1.8.2 lifecycle_1.0.4
[69] carData_3.0-5 SummarizedExperiment_1.30.2 SparseArray_1.4.8 Rtsne_0.17
[73] grid_4.4.0 promises_1.3.0 crayon_1.5.3 shinydashboard_0.7.2
[77] miniUI_0.1.1.1 lattice_0.22-6 msigdbr_7.5.1 cowplot_1.1.3
[81] knitr_1.48 pillar_1.9.0 ComplexHeatmap_2.20.0 GenomicRanges_1.56.1
[85] rjson_0.2.22 future.apply_1.11.2 codetools_0.2-19 leiden_0.4.3.1
[89] glue_1.7.0 V8_5.0.0 spatstat.univar_3.0-1 data.table_1.16.0
[93] remotes_2.5.0 vctrs_0.6.5 png_0.1-8 gtable_0.3.5
[97] assertthat_0.2.1 cachem_1.1.0 openxlsx_4.2.5.2 xfun_0.47
[101] S4Arrays_1.4.1 mime_0.12 rsconnect_1.3.1 survival_3.7-0
[105] SingleCellExperiment_1.26.0 iterators_1.0.14 units_0.8-5 ellipsis_0.3.2
[109] fitdistrplus_1.2-1 ROCR_1.0-11 nlme_3.1-166 usethis_3.0.0
[113] bit64_4.0.5 progress_1.2.3 RcppAnnoy_0.0.22 GenomeInfoDb_1.40.1
[117] bslib_0.8.0 irlba_2.3.5.1 KernSmooth_2.23-24 DBI_1.2.3
[121] colorspace_2.1-1 BiocGenerics_0.50.0 tidyselect_1.2.1 processx_3.8.4
[125] bit_4.0.5 compiler_4.4.0 curl_5.2.2 hdf5r_1.3.11
[129] xml2_1.3.6 desc_1.4.3 DelayedArray_0.30.1 plotly_4.10.2
[133] scales_1.3.0 classInt_0.4-10 lmtest_0.9-40 callr_3.7.6
[137] tiff_0.1-12 digest_0.6.37 goftest_1.2-3 fftwtools_0.9-11
[141] spatstat.utils_3.1-0 rmarkdown_2.28 XVector_0.44.0 htmltools_0.5.8.1
[145] pkgconfig_2.0.3 jpeg_0.1-10 MatrixGenerics_1.17.0 fastmap_1.2.0
[149] rlang_1.1.4 GlobalOptions_0.1.2 htmlwidgets_1.6.4 UCSC.utils_1.0.0
[153] jquerylib_0.1.4 ggh4x_0.2.8 farver_2.1.2 zoo_1.8-12
[157] jsonlite_1.8.8 R.oo_1.25.0 RCurl_1.98-1.16 magrittr_2.0.3
[161] kableExtra_1.4.0 GenomeInfoDbData_1.2.12 patchwork_1.2.0 munsell_0.5.1
[165] Rcpp_1.0.13 babelgene_22.9 reticulate_1.39.0 stringi_1.8.4
[169] zlibbioc_1.50.0 MASS_7.3-61 plyr_1.8.9 pkgbuild_1.4.4
[173] parallel_4.4.0 listenv_0.9.1 ggrepel_0.9.6 deldir_2.0-4
[177] splines_4.4.0 tensor_1.5 hms_1.1.3 circlize_0.4.16
[181] locfit_1.5-9.10 ps_1.7.7 igraph_2.0.3 ggpubr_0.6.0
[185] spatstat.geom_3.3-2 ggsignif_0.6.4 reshape2_1.4.4 stats4_4.4.0
[189] pkgload_1.4.0 evaluate_0.24.0 BiocManager_1.30.25 tweenr_2.0.3
[193] tzdb_0.4.0 foreach_1.5.2 httpuv_1.6.15 RANN_2.6.2
[197] polyclip_1.10-7 future_1.34.0 clue_0.3-65 scattermore_1.2
[201] ggforce_0.4.2 rsvd_1.0.5 broom_1.0.6 xtable_1.8-4
[205] e1071_1.7-14 rstatix_0.7.2 later_1.3.2 class_7.3-22
[209] ragg_1.3.2 viridisLite_0.4.2 confuns_1.0.3 hypeR_2.2.0
[213] memoise_2.0.1 IRanges_2.38.1 cluster_2.1.4 shinyWidgets_0.8.0
[217] keys_0.1.1 timechange_0.3.0 globals_0.16.3 concaveman_1.1.0

[kueckelj]

Hi, this is due to the fact that SPATA2 deals with images in "cartesian coordinate" space. You can use the flip functions to revert that effect. I will update the initiateSpataObjectVisium() function to include this with a simple argument in the next version release. Till then:

object <- flipCoordinates(object, axis = "h") for(img_name in getImageNames(object){ object <- flipImage(object, axis = "h", img_name = img_name) }

The for loop is not necessary if you have only one image registered.

Does that help ?

[kueckelj]

You said "problems" as in "multiple problems". Anything else that you noticed?

[FelixZ95]

Thank you for your reply and code. I think it may be because I ignored some transformations of the coordinate axis, which caused the error. Now there is no error after the correct transformation of the coordinate axis. Looking forward to the new version.

[kueckelj]

Happy to help.