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-pc-linux-gnu (64-bit)
## Running under: Ubuntu 22.04.3 LTS
## 
## Matrix products: default
## BLAS:   /home/biocbuild/bbs-3.18-bioc/R/lib/libRblas.so 
## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.10.0
## 
## locale:
##  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
##  [3] LC_TIME=en_GB              LC_COLLATE=C              
##  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
##  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
##  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
## 
## time zone: America/New_York
## tzcode source: system (glibc)
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
## [1] CytoPipeline_1.2.0 BiocStyle_2.30.0  
## 
## loaded via a namespace (and not attached):
##   [1] changepoint_2.2.4     tidyselect_1.2.0      farver_2.1.1         
##   [4] dplyr_1.1.3           blob_1.2.4            filelock_1.0.2       
##   [7] fastmap_1.1.1         BiocFileCache_2.10.0  XML_3.99-0.14        
##  [10] digest_0.6.33         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_0.4.7            tools_4.3.1          
##  [19] utf8_1.2.4            yaml_2.3.7            data.table_1.14.8    
##  [22] knitr_1.44            labeling_0.4.3        bit_4.0.5            
##  [25] curl_5.1.0            diagram_1.6.5         plyr_1.8.9           
##  [28] RColorBrewer_1.1-3    withr_2.5.1           purrr_1.0.2          
##  [31] RProtoBufLib_2.14.0   BiocGenerics_0.48.0   PeacoQC_1.12.0       
##  [34] grid_4.3.1            stats4_4.3.1          fansi_1.0.5          
##  [37] flowAI_1.32.0         colorspace_2.1-0      ggplot2_3.4.4        
##  [40] scales_1.2.1          iterators_1.0.14      cli_3.6.1            
##  [43] rmarkdown_2.25        crayon_1.5.2          ncdfFlow_2.48.0      
##  [46] generics_0.1.3        reshape2_1.4.4        httr_1.4.7           
##  [49] rjson_0.2.21          DBI_1.1.3             cachem_1.0.8         
##  [52] flowCore_2.14.0       stringr_1.5.0         zlibbioc_1.48.0      
##  [55] parallel_4.3.1        BiocManager_1.30.22   matrixStats_1.0.0    
##  [58] vctrs_0.6.4           jsonlite_1.8.7        cytolib_2.14.0       
##  [61] bookdown_0.36         IRanges_2.36.0        GetoptLong_1.0.5     
##  [64] S4Vectors_0.40.0      bit64_4.0.5           clue_0.3-65          
##  [67] Rgraphviz_2.46.0      magick_2.8.1          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_0.3.4         
##  [76] shape_1.4.6           ggcyto_1.30.0         ComplexHeatmap_2.18.0
##  [79] munsell_0.5.0         tibble_3.2.1          pillar_1.9.0         
##  [82] htmltools_0.5.6.1     graph_1.80.0          circlize_0.4.15      
##  [85] R6_2.5.1              dbplyr_2.3.4          doParallel_1.0.17    
##  [88] evaluate_0.22         flowWorkspace_4.14.0  lattice_0.22-5       
##  [91] Biobase_2.62.0        png_0.1-8             memoise_2.0.1        
##  [94] bslib_0.5.1           Rcpp_1.0.11           gridExtra_2.3        
##  [97] xfun_0.40             zoo_1.8-12            pkgconfig_2.0.3      
## [100] GlobalOptions_0.1.2