# Demonstration of the CytoPipeline R package suite functionalities

Philippe Hauchamps and Laurent Gatto

#### 4 July 2023

#### 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 1.0.2

# 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 4.3.1 (2023-06-16)
    ## Platform: x86_64-apple-darwin20 (64-bit)
    ## Running under: macOS Monterey 12.6.4
    ##
    ## Matrix products: default
    ## BLAS:   /Library/Frameworks/R.framework/Versions/4.3-x86_64/Resources/lib/libRblas.0.dylib
    ## LAPACK: /Library/Frameworks/R.framework/Versions/4.3-x86_64/Resources/lib/libRlapack.dylib;  LAPACK version 3.11.0
    ##
    ## locale:
    ## [1] C/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
    ##
    ## time zone: America/New_York
    ## tzcode source: internal
    ##
    ## attached base packages:
    ## [1] stats     graphics  grDevices utils     datasets  methods   base
    ##
    ## other attached packages:
    ## [1] CytoPipeline_1.0.2 BiocStyle_2.28.0
    ##
    ## loaded via a namespace (and not attached):
    ##   [1] changepoint_2.2.4     tidyselect_1.2.0      farver_2.1.1
    ##   [4] dplyr_1.1.2           blob_1.2.4            filelock_1.0.2
    ##   [7] fastmap_1.1.1         BiocFileCache_2.8.0   XML_3.99-0.14
    ##  [10] digest_0.6.32         lifecycle_1.0.3       cluster_2.1.4
    ##  [13] RSQLite_2.3.1         magrittr_2.0.3        compiler_4.3.1
    ##  [16] rlang_1.1.1           sass_0.4.6            tools_4.3.1
    ##  [19] utf8_1.2.3            yaml_2.3.7            data.table_1.14.8
    ##  [22] knitr_1.43            labeling_0.4.2        bit_4.0.5
    ##  [25] curl_5.0.1            diagram_1.6.5         plyr_1.8.8
    ##  [28] RColorBrewer_1.1-3    withr_2.5.0           purrr_1.0.1
    ##  [31] RProtoBufLib_2.12.0   BiocGenerics_0.46.0   PeacoQC_1.10.0
    ##  [34] grid_4.3.1            stats4_4.3.1          fansi_1.0.4
    ##  [37] flowAI_1.30.0         colorspace_2.1-0      ggplot2_3.4.2
    ##  [40] scales_1.2.1          iterators_1.0.14      cli_3.6.1
    ##  [43] rmarkdown_2.23        crayon_1.5.2          ncdfFlow_2.46.0
    ##  [46] generics_0.1.3        reshape2_1.4.4        httr_1.4.6
    ##  [49] rjson_0.2.21          DBI_1.1.3             cachem_1.0.8
    ##  [52] flowCore_2.12.0       stringr_1.5.0         zlibbioc_1.46.0
    ##  [55] parallel_4.3.1        BiocManager_1.30.21   matrixStats_1.0.0
    ##  [58] vctrs_0.6.3           jsonlite_1.8.7        cytolib_2.12.0
    ##  [61] bookdown_0.34         IRanges_2.34.1        GetoptLong_1.0.5
    ##  [64] S4Vectors_0.38.1      bit64_4.0.5           clue_0.3-64
    ##  [67] Rgraphviz_2.44.0      magick_2.7.4          foreach_1.5.2
    ##  [70] jquerylib_0.1.4       hexbin_1.28.3         glue_1.6.2
    ##  [73] codetools_0.2-19      stringi_1.7.12        gtable_0.3.3
    ##  [76] shape_1.4.6           ggcyto_1.28.0         ComplexHeatmap_2.16.0
    ##  [79] munsell_0.5.0         tibble_3.2.1          pillar_1.9.0
    ##  [82] htmltools_0.5.5       graph_1.78.0          circlize_0.4.15
    ##  [85] R6_2.5.1              dbplyr_2.3.2          doParallel_1.0.17
    ##  [88] evaluate_0.21         flowWorkspace_4.12.0  lattice_0.21-8
    ##  [91] Biobase_2.60.0        highr_0.10            png_0.1-8
    ##  [94] memoise_2.0.1         bslib_0.5.0           Rcpp_1.0.10
    ##  [97] gridExtra_2.3         xfun_0.39             zoo_1.8-12
    ## [100] pkgconfig_2.0.3       GlobalOptions_0.1.2