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I am working through the vignette to analyze my dataset; however, I am stuck at this step:
show all NTC values, Freq = # of Segments with a given NTC count:
kable(table(NTC_Count = sData(demoData)$NTC),
col.names = c("NTC Count", "# of Segments"))
Inspecting my Nanostringgeomx object, I do not see the NTC values under protocolData. It is there in the demo data but not my own. My annotation file does contain NTCs and I loaded the NTC .dcc files. I am not sure what I am missing.
Thanks!
R version 4.3.1 (2023-06-16 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19044)
Hi,
I am working through the vignette to analyze my dataset; however, I am stuck at this step:
show all NTC values, Freq = # of Segments with a given NTC count:
kable(table(NTC_Count = sData(demoData)$NTC),
col.names = c("NTC Count", "# of Segments"))
Inspecting my Nanostringgeomx object, I do not see the NTC values under protocolData. It is there in the demo data but not my own. My annotation file does contain NTCs and I loaded the NTC .dcc files. I am not sure what I am missing.
Thanks!
R version 4.3.1 (2023-06-16 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19044)
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.utf8 LC_CTYPE=English_United States.utf8
[3] LC_MONETARY=English_United States.utf8 LC_NUMERIC=C
[5] LC_TIME=English_United States.utf8
time zone: America/Chicago
tzcode source: internal
attached base packages:
[1] stats4 stats graphics grDevices utils datasets methods base
other attached packages:
[1] ggforce_0.4.1 dplyr_1.0.8 knitr_1.43 GeoMxWorkflows_1.6.0
[5] GeomxTools_3.4.0 NanoStringNCTools_1.8.0 ggplot2_3.4.2 S4Vectors_0.38.1
[9] Biobase_2.60.0 BiocGenerics_0.46.0
loaded via a namespace (and not attached):
[1] RColorBrewer_1.1-3 jsonlite_1.8.7 rstudioapi_0.15.0 umap_0.2.10.0
[5] magrittr_2.0.3 ggbeeswarm_0.7.2 rmarkdown_2.23 farver_2.1.1
[9] nloptr_2.0.3 fs_1.6.2 zlibbioc_1.46.0 vctrs_0.6.3
[13] memoise_2.0.1 minqa_1.2.5 RCurl_1.98-1.12 askpass_1.1
[17] htmltools_0.5.5 usethis_2.2.2 cellranger_1.1.0 parallelly_1.36.0
[21] htmlwidgets_1.6.2 plyr_1.8.8 cachem_1.0.8 uuid_1.1-0
[25] mime_0.12 lifecycle_1.0.3 pkgconfig_2.0.3 Matrix_1.6-0
[29] R6_2.5.1 fastmap_1.1.1 GenomeInfoDbData_1.2.10 future_1.33.0
[33] shiny_1.7.4.1 digest_0.6.29 numDeriv_2016.8-1.1 colorspace_2.1-0
[37] GGally_2.1.2 reshape_0.8.9 maftools_2.10.05 ps_1.7.5
[41] RSpectra_0.16-1 pkgload_1.3.2.1 labeling_0.4.2 progressr_0.13.0
[45] fansi_1.0.4 polyclip_1.10-4 compiler_4.3.1 remotes_2.4.2.1
[49] withr_2.5.0 DBI_1.1.3 pkgbuild_1.4.2 MASS_7.3-60
[53] openssl_2.1.0 sessioninfo_1.2.2 rjson_0.2.21 ggsci_3.0.0
[57] tools_4.3.1 vipor_0.4.5 beeswarm_0.4.0 httpuv_1.6.11
[61] future.apply_1.11.0 glue_1.6.2 callr_3.7.3 nlme_3.1-162
[65] promises_1.2.0.1 grid_4.3.1 Rtsne_0.16 cluster_2.1.4
[69] reshape2_1.4.4 generics_0.1.3 gtable_0.3.3 data.table_1.14.2
[73] sp_2.0-0 utf8_1.2.3 XVector_0.40.0 ggrepel_0.9.3
[77] pillar_1.9.0 stringr_1.5.0 later_1.3.1 splines_4.3.1
[81] tweenr_2.0.2 lattice_0.21-8 survival_3.3-1 tidyselect_1.2.0
[85] Biostrings_2.68.1 miniUI_0.1.1.1 IRanges_2.34.1 xfun_0.39
[89] devtools_2.4.5 pheatmap_1.0.12 stringi_1.7.12 yaml_2.3.7
[93] boot_1.3-28.1 evaluate_0.21 codetools_0.2-19 tibble_3.2.1
[97] BiocManager_1.30.16 cli_3.6.1 reticulate_1.30 xtable_1.8-4
[101] systemfonts_1.0.4 munsell_0.5.0 processx_3.8.2 Rcpp_1.0.11
[105] GenomeInfoDb_1.36.1 readxl_1.4.3 globals_0.16.2 EnvStats_2.8.0
[109] outliers_0.15 png_0.1-8 parallel_4.3.1 ellipsis_0.3.2
[113] prettyunits_1.1.1 profvis_0.3.8 urlchecker_1.0.1 bitops_1.0-7
[117] lme4_1.1-34 listenv_0.9.0 ggthemes_4.2.4 ggiraph_0.8.7
[121] lmerTest_3.1-3 scales_1.2.1 SeuratObject_4.1.3 purrr_0.3.4
[125] crayon_1.5.2 BiocStyle_2.28.0 rlang_1.1.1 cowplot_1.1.1
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