Marking Frequency % inside Barplot stacks about scpubr HOT 5 CLOSED

Hi @athulmenon,

Thanks for using my package!

This is something I am working on for update v2.0.0. However, and sadly, displaying the proportions in the plot will only work if the fractions are sufficiently big for the numbers to be seen. Otherwise, they will collapse on top of each other. An alternative is to repel the text/labels, but it also generates quite noisy visualizations.

Therefore, I decided to add the option to display the total number of observations with add.n parameter when position = fill is set, so that one can get an insight on the observations per bar.

I am also adding a return_data parameter that will output a tibble with the counts and proportions displayed in the plot. This can then be used as supplementary data that goes along with the bar plot, if used for a publication.

I hope this answer helps you! All these changes will roll out when the next update is ready. Until then, you can access them via GitHub downloading the last commit. However, bear in mind that the commit versions might still have bugs and be in experimental phase!

Best,
Enrique

from scpubr.

Hi @enblacar,

Thank you for your reply.

I installed the recent commit and could generate the barplots without any issues.
But when I tried return_data = T it throws an error as below.
Error: 'reframe' is not an exported object from 'namespace:dplyr'

I made sure dplyr is loaded to the R and updated. Do you have any suggestions on how to use return_data?

session_info()
R version 4.1.1 (2021-08-10)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19045)

Matrix products: default

locale:
[1] LC_COLLATE=English_United Kingdom.1252 LC_CTYPE=English_United Kingdom.1252 LC_MONETARY=English_United Kingdom.1252
[4] LC_NUMERIC=C LC_TIME=English_United Kingdom.1252

attached base packages:
[1] stats4 stats graphics grDevices utils datasets methods base

other attached packages:
[1] org.Mm.eg.db_3.14.0 dplyr_1.0.10 limma_3.50.3 metap_1.8
[5] multtest_2.50.0 sctransform_0.3.5 purrr_0.3.5 gridExtra_2.3
[9] celldex_1.4.0 SingleR_1.8.1 ensembldb_2.18.4 AnnotationFilter_1.18.0
[13] GenomicFeatures_1.46.5 AnnotationDbi_1.56.2 AnnotationHub_3.2.2 BiocFileCache_2.2.1
[17] dbplyr_2.2.1 RCurl_1.98-1.8 cowplot_1.1.1 scales_1.2.1
[21] Matrix_1.5-1 SingleCellExperiment_1.16.0 SummarizedExperiment_1.24.0 Biobase_2.54.0
[25] GenomicRanges_1.46.1 GenomeInfoDb_1.30.1 IRanges_2.28.0 S4Vectors_0.32.4
[29] BiocGenerics_0.40.0 MatrixGenerics_1.6.0 matrixStats_0.62.0 patchwork_1.1.2
[33] ggplot2_3.4.0 BiocParallel_1.28.3 scDblFinder_1.8.0 sp_1.5-0
[37] SeuratObject_4.1.2 Seurat_4.2.0 SCpubr_2.0.0.9000

loaded via a namespace (and not attached):
[1] rsvd_1.0.5 ica_1.0-3 svglite_2.1.0 ps_1.7.2
[5] Rsamtools_2.10.0 lmtest_0.9-40 rprojroot_2.0.3 crayon_1.5.2
[9] spatstat.core_2.4-4 rbibutils_2.2.11 MASS_7.3-54 nlme_3.1-152
[13] rlang_1.0.6 XVector_0.34.0 ROCR_1.0-11 irlba_2.3.5.1
[17] callr_3.7.3 scater_1.22.0 filelock_1.0.2 xgboost_1.6.0.1
[21] stringfish_0.15.7 qs_0.25.4 rjson_0.2.21 bit64_4.0.5
[25] glue_1.6.2 pheatmap_1.0.12 parallel_4.1.1 processx_3.8.0
[29] vipor_0.4.5 spatstat.sparse_3.0-0 spatstat.geom_3.0-3 tidyselect_1.2.0
[33] usethis_2.1.6 fitdistrplus_1.1-8 XML_3.99-0.12 tidyr_1.2.1
[37] zoo_1.8-11 qqconf_1.3.0 GenomicAlignments_1.30.0 distributional_0.3.2
[41] xtable_1.8-4 magrittr_2.0.3 evaluate_0.17 Rdpack_2.4
[45] scuttle_1.4.0 cli_3.4.1 zlibbioc_1.40.0 sn_2.1.0
[49] rstudioapi_0.14 miniUI_0.1.1.1 rpart_4.1-15 mathjaxr_1.6-0
[53] shiny_1.7.3 BiocSingular_1.10.0 xfun_0.34 pkgbuild_1.4.0
[57] cluster_2.1.2 KEGGREST_1.34.0 tibble_3.1.8 interactiveDisplayBase_1.32.0
[61] ggrepel_0.9.1 listenv_0.8.0 Biostrings_2.62.0 png_0.1-7
[65] future_1.28.0 withr_2.5.0 bitops_1.0-7 plyr_1.8.7
[69] dqrng_0.3.0 pillar_1.8.1 RcppParallel_5.1.5 GlobalOptions_0.1.2
[73] cachem_1.0.6 multcomp_1.4-20 fs_1.5.2 DelayedMatrixStats_1.16.0
[77] vctrs_0.5.0 ellipsis_0.3.2 generics_0.1.3 devtools_2.4.5
[81] RApiSerialize_0.1.2 tools_4.1.1 beeswarm_0.4.0 munsell_0.5.0
[85] DelayedArray_0.20.0 fastmap_1.1.0 compiler_4.1.1 pkgload_1.3.2
[89] abind_1.4-5 httpuv_1.6.6 rtracklayer_1.54.0 ExperimentHub_2.2.1
[93] sessioninfo_1.2.2 plotly_4.10.0 rgeos_0.5-9 GenomeInfoDbData_1.2.7
[97] edgeR_3.36.0 lattice_0.20-44 deldir_1.0-6 mutoss_0.1-12
[101] utf8_1.2.2 later_1.3.0 jsonlite_1.8.3 ScaledMatrix_1.2.0
[105] pbapply_1.5-0 sparseMatrixStats_1.6.0 lazyeval_0.2.2 promises_1.2.0.1
[109] goftest_1.2-3 spatstat.utils_3.0-1 reticulate_1.26 sandwich_3.0-2
[113] rmarkdown_2.17 openxlsx_4.2.5.2 statmod_1.4.37 Rtsne_0.16
[117] forcats_0.5.2 uwot_0.1.14 igraph_1.3.5 plotrix_3.8-2
[121] survival_3.2-11 numDeriv_2016.8-1.1 yaml_2.3.6 systemfonts_1.0.4
[125] htmltools_0.5.3 memoise_2.0.1 profvis_0.3.7 BiocIO_1.4.0
[129] locfit_1.5-9.6 here_1.0.1 viridisLite_0.4.1 digest_0.6.30
[133] assertthat_0.2.1 mime_0.12 rappdirs_0.3.3 RSQLite_2.2.18
[137] yulab.utils_0.0.5 future.apply_1.9.1 remotes_2.4.2 data.table_1.14.4
[141] urlchecker_1.0.1 blob_1.2.3 splines_4.1.1 labeling_0.4.2
[145] ProtGenerics_1.26.0 hms_1.1.2 colorspace_2.0-3 BiocManager_1.30.19
[149] mnormt_2.1.1 ggbeeswarm_0.6.0 shape_1.4.6 ggrastr_1.0.1
[153] Rcpp_1.0.9 RANN_2.6.1 mvtnorm_1.1-3 circlize_0.4.15
[157] fansi_1.0.3 parallelly_1.32.1 R6_2.5.1 grid_4.1.1
[161] ggridges_0.5.4 lifecycle_1.0.3 zip_2.2.2 TFisher_0.2.0
[165] bluster_1.4.0 curl_4.3.3 ggsignif_0.6.4 leiden_0.4.3
[169] TH.data_1.1-1 desc_1.4.2 RcppAnnoy_0.0.20 RColorBrewer_1.1-3
[173] stringr_1.4.1 htmlwidgets_1.5.4 beachmat_2.10.0 polyclip_1.10-4
[177] biomaRt_2.50.3 gridGraphics_0.5-1 mgcv_1.8-36 globals_0.16.1
[181] spatstat.random_2.2-0 progressr_0.11.0 codetools_0.2-18 metapod_1.2.0
[185] prettyunits_1.1.1 ggdist_3.2.1 gtable_0.3.1 DBI_1.1.3
[189] ggalluvial_0.12.3 tensor_1.5 httr_1.4.4 KernSmooth_2.23-20
[193] stringi_1.7.8 progress_1.2.2 reshape2_1.4.4 farver_2.1.1
[197] viridis_0.6.2 xml2_1.3.3 BiocNeighbors_1.12.0 restfulr_0.0.15
[201] ggplotify_0.1.0 scattermore_0.8 BiocVersion_3.14.0 decoupleR_2.3.3
[205] scran_1.22.1 bit_4.0.4 spatstat.data_3.0-0 pkgconfig_2.0.3
[209] knitr_1.40 `

Regards,
Athul

from scpubr.

Hi @enblacar

The issue is solved with updating dplyr v1.1

Regards,
Athul

from scpubr.

Hi @athulmenon,

Yes, I was gonna mention that you should update dplyr.

For the return_data, just assign the call to SCpubr::do_BarPlot() to a variable and you should retrieve an output list with the plot and the data.frame with the data you need.

Please also consider updating to this commit:

devtools::install_github("enblacar/SCpubr", ref = "0cd9dfd")
# Reload R Session
detach("package:SCpubr")
library(SCpubr)

Let me know if it works!
Enrique

from scpubr.

Thanks @enblacar,

It worked!

Regards,
Athul

from scpubr.