# Demonstration of the CytoPipeline R package suite functionalities

Philippe Hauchamps and Laurent Gatto

#### 1 May 2024

#### Abstract

This vignette provides links to videos demonstrating some of the functionalities of CytoPipeline R package suite. It is distributed, as well as the accompanying videos, under a CC BY-SA license.

#### Package

CytoPipeline 1.4.0

# 1 Introduction

# 2 Background information

# 3 Illustrating dataset

# 4 Specifying the pipeline

# 5 Running the pipeline

# 6 Visualizing the results

# 7 Comparing pipelines

# 8 Example with two different QC methods

# 9 Visualizing scale transformations

# 10 Defining technical run parameters

# Session information

    ## R version 4.4.0 beta (2024-04-15 r86425 ucrt)
    ## Platform: x86_64-w64-mingw32/x64
    ## Running under: Windows Server 2022 x64 (build 20348)
    ##
    ## Matrix products: default
    ##
    ##
    ## locale:
    ## [1] LC_COLLATE=C
    ## [2] LC_CTYPE=English_United States.utf8
    ## [3] LC_MONETARY=English_United States.utf8
    ## [4] LC_NUMERIC=C
    ## [5] LC_TIME=English_United States.utf8
    ##
    ## time zone: America/New_York
    ## tzcode source: internal
    ##
    ## attached base packages:
    ## [1] stats     graphics  grDevices utils     datasets  methods   base
    ##
    ## other attached packages:
    ## [1] ggplot2_3.5.1      reshape2_1.4.4     CytoPipeline_1.4.0 BiocStyle_2.32.0
    ##
    ## loaded via a namespace (and not attached):
    ##   [1] changepoint_2.2.4     tidyselect_1.2.1      farver_2.1.1
    ##   [4] dplyr_1.1.4           blob_1.2.4            filelock_1.0.3
    ##   [7] fastmap_1.1.1         BiocFileCache_2.12.0  XML_3.99-0.16.1
    ##  [10] digest_0.6.35         lifecycle_1.0.4       cluster_2.1.6
    ##  [13] RSQLite_2.3.6         magrittr_2.0.3        compiler_4.4.0
    ##  [16] rlang_1.1.3           sass_0.4.9            tools_4.4.0
    ##  [19] utf8_1.2.4            yaml_2.3.8            data.table_1.15.4
    ##  [22] knitr_1.46            labeling_0.4.3        bit_4.0.5
    ##  [25] curl_5.2.1            diagram_1.6.5         plyr_1.8.9
    ##  [28] RColorBrewer_1.1-3    withr_3.0.0           purrr_1.0.2
    ##  [31] RProtoBufLib_2.16.0   BiocGenerics_0.50.0   PeacoQC_1.14.0
    ##  [34] grid_4.4.0            stats4_4.4.0          fansi_1.0.6
    ##  [37] flowAI_1.34.0         colorspace_2.1-0      scales_1.3.0
    ##  [40] iterators_1.0.14      tinytex_0.50          cli_3.6.2
    ##  [43] rmarkdown_2.26        crayon_1.5.2          ncdfFlow_2.50.0
    ##  [46] generics_0.1.3        httr_1.4.7            rjson_0.2.21
    ##  [49] DBI_1.2.2             cachem_1.0.8          flowCore_2.16.0
    ##  [52] stringr_1.5.1         zlibbioc_1.50.0       parallel_4.4.0
    ##  [55] BiocManager_1.30.22   matrixStats_1.3.0     vctrs_0.6.5
    ##  [58] jsonlite_1.8.8        cytolib_2.16.0        bookdown_0.39
    ##  [61] IRanges_2.38.0        GetoptLong_1.0.5      S4Vectors_0.42.0
    ##  [64] bit64_4.0.5           clue_0.3-65           Rgraphviz_2.48.0
    ##  [67] magick_2.8.3          foreach_1.5.2         jquerylib_0.1.4
    ##  [70] hexbin_1.28.3         glue_1.7.0            codetools_0.2-20
    ##  [73] stringi_1.8.3         gtable_0.3.5          shape_1.4.6.1
    ##  [76] ggcyto_1.32.0         ComplexHeatmap_2.20.0 munsell_0.5.1
    ##  [79] tibble_3.2.1          pillar_1.9.0          htmltools_0.5.8.1
    ##  [82] graph_1.82.0          circlize_0.4.16       R6_2.5.1
    ##  [85] dbplyr_2.5.0          doParallel_1.0.17     evaluate_0.23
    ##  [88] flowWorkspace_4.16.0  lattice_0.22-6        Biobase_2.64.0
    ##  [91] highr_0.10            png_0.1-8             memoise_2.0.1
    ##  [94] bslib_0.7.0           Rcpp_1.0.12           gridExtra_2.3
    ##  [97] xfun_0.43             zoo_1.8-12            pkgconfig_2.0.3
    ## [100] GlobalOptions_0.1.2