BOBaFIT

Gaia Mazzocchetti1*

1University of Bologna - DIMES

*bioinformatics.seragnoli@gmail.com

2025-10-29

Abstract

Good practices for BOBaFIT package

Package

BOBaFIT 1.14.0

• 1 Introduction
• 2 Data
• 3 BOBaFIT Workflow
  • 3.1 ComputeNormalChromosome
  • 3.2 DRrefit
    • 3.2.1 The Dataframes
  • 3.3 DRrefit_plot
• 4 PlotChrCluster
  • 4.1 The Dataframes
• Session info
• Reference

1 Introduction

The R package BoBafit is composed of four functions which allow the refit and the recalibration of copy number profile of tumor sample. In particular, the package was built to check, and possibly correct, the diploid regions. The wrong diploid region is a phenomenon that very often affects the profiles of samples with a very complex karyotype.

The principal and refitting function was namedDRrefit, which - throughout a chromosome clustering method and a list of unaltered chromosomes (chromosome list) - recalibrates the copy number values. BoBafit also contains three secondary functions:ComputeNormalChromosome, which generates the chromosome list;PlotChrCluster, where is possible to visualize the cluster; andPopeye, which affixes its chromosomal arm to each segment (see in “Data Preparation” vignette).

2 Data

The package checks the diploid region assessment working on pre-estimated segment information, as the copy number and their position. We included a data setTCGA_BRCA_CN_segments where are showed all the information necessary. The data correspond to segments about 100 breast tumors samples obtained by the project TCGA-BRCA(Tomczak, Czerwińska, and Wiznerowicz2015). In the “Data Preparation” vingnette is shown how we download and prepare the dataset for the following analysis.

## Warning: replacing previous import 'ggplot2::geom_segment' by## 'ggbio::geom_segment' when loading 'BOBaFIT'

3 BOBaFIT Workflow

Once the dataset has been prepared, the next step is to generate the chromosome list. The chromosome list is a vector containing all chromosomal arm which are the least affected by SCNAs in the tumor analyzed. Together with the clustering, the chromosome list is one the operating principles to rewrite the diploid region. The list can be manually created or by using the functionComputeNormalChromosome. We suggest these two sequential steps to allow the right refit and recalibration of sample’s diploid region:

1. ComputeNormalChromosome()

2. DRrefit()

Here we performed this analysis workflow on the datasetTCGA_BRCA_CN_segments described above.

chr_list

results <- DRrefit (segments_chort = TCGA_BRCA_CN_segments, chrlist = chr_list)

results$corrected_segments[1,]

results$report[1,]

corrected_segments <- results$corrected_segmentsreport <- results$report

# the plot is diplayed on the R viewerDRrefit_plot(corrected_segments = corrected_segments,             DRrefit_report = report,              plot_viewer = TRUE,              plot_save = FALSE )# how to save the plot DRrefit_plot(corrected_segments = corrected_segments,             DRrefit_report = report,              plot_save = TRUE, plot_format = "pdf", plot_path = "/my_path" )

## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.## ℹ Please use `linewidth` instead.## ℹ The deprecated feature was likely used in the ggbio package.##   Please report the issue at <https://github.com/lawremi/ggbio/issues>.## This warning is displayed once every 8 hours.## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was## generated.

## Warning: The `size` argument of `element_rect()` is deprecated as of ggplot2 3.4.0.## ℹ Please use the `linewidth` argument instead.## ℹ The deprecated feature was likely used in the BOBaFIT package.##   Please report the issue at##   <https://github.com/andrea-poletti-unibo/BOBaFIT/issues>.## This warning is displayed once every 8 hours.## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was## generated.

## Warning: Removed 81 rows containing missing values or values outside the scale range## (`geom_segment()`).

## Warning: Removed 82 rows containing missing values or values outside the scale range## (`geom_segment()`).

## Warning: Removed 52 rows containing missing values or values outside the scale range## (`geom_segment()`).

## Warning: Removed 48 rows containing missing values or values outside the scale range## (`geom_segment()`).

4 PlotChrCluster

Another accessory function isPlotChrCluster. It can be used to visualize the chromosomal cluster in a single sample or in a sample cohort. The input data is always a .tsv file, as the data frameTCGA_BRCA_CN_segments. The option ofclust_method argument are the same ofDRrefit(“ward.D”, “ward.D2”, “single”, “complete”, “average”, “mcquitty”, “median”, “centroid” and “kmeans”).

Cluster <- PlotChrCluster(segs = TCGA_BRCA_CN_segments,                       clust_method = "ward.D2",                       plot_output= TRUE)

We suggest to store the output on a variable (in this example we useCluster) to view and possibly save the data frame generated. ThePlotCuster will automatically save the plot in the folder indicated by the variablepath of the argumentplot_path.

In thePlotChrCluster plot, the chromosomal arms are labeled and colored according to the cluster they belong to. The y-axis reports the arm CN.

head(Cluster$report) #select plot table per samplehead(Cluster$plot_tables$`01428281-1653-4839-b5cf-167bc62eb147`)

knitr::kable(head(Cluster$report))

#select plot table per sampleknitr::kable(head(Cluster$plot_tables$`01428281-1653-4839-b5cf-167bc62eb147`))

Session info

## R version 4.5.1 Patched (2025-08-23 r88802)## Platform: x86_64-pc-linux-gnu## Running under: Ubuntu 24.04.3 LTS## ## Matrix products: default## BLAS:   /home/biocbuild/bbs-3.22-bioc/R/lib/libRblas.so ## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.0  LAPACK version 3.12.0## ## 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] dplyr_1.1.4      BOBaFIT_1.14.0   BiocStyle_2.38.0## ## loaded via a namespace (and not attached):##   [1] DBI_1.2.3                   bitops_1.0-9               ##   [3] RBGL_1.86.0                 gridExtra_2.3              ##   [5] rlang_1.1.6                 magrittr_2.0.4             ##   [7] biovizBase_1.58.0           matrixStats_1.5.0          ##   [9] compiler_4.5.1              RSQLite_2.4.3              ##  [11] GenomicFeatures_1.62.0      png_0.1-8                  ##  [13] vctrs_0.6.5                 reshape2_1.4.4             ##  [15] ProtGenerics_1.42.0         stringr_1.5.2              ##  [17] pkgconfig_2.0.3             crayon_1.5.3               ##  [19] fastmap_1.2.0               magick_2.9.0               ##  [21] backports_1.5.0             XVector_0.50.0             ##  [23] labeling_0.4.3              Rsamtools_2.26.0           ##  [25] rmarkdown_2.30              graph_1.88.0               ##  [27] UCSC.utils_1.6.0            tinytex_0.57               ##  [29] purrr_1.1.0                 bit_4.6.0                  ##  [31] xfun_0.53                   cachem_1.1.0               ##  [33] cigarillo_1.0.0             GenomeInfoDb_1.46.0        ##  [35] jsonlite_2.0.0              blob_1.2.4                 ##  [37] DelayedArray_0.36.0         tweenr_2.0.3               ##  [39] BiocParallel_1.44.0         parallel_4.5.1             ##  [41] cluster_2.1.8.1             plyranges_1.30.0           ##  [43] VariantAnnotation_1.56.0    R6_2.6.1                   ##  [45] bslib_0.9.0                 stringi_1.8.7              ##  [47] RColorBrewer_1.1-3          rtracklayer_1.70.0         ##  [49] rpart_4.1.24                GenomicRanges_1.62.0       ##  [51] jquerylib_0.1.4             Rcpp_1.1.0                 ##  [53] Seqinfo_1.0.0               bookdown_0.45              ##  [55] SummarizedExperiment_1.40.0 knitr_1.50                 ##  [57] base64enc_0.1-3             IRanges_2.44.0             ##  [59] Matrix_1.7-4                nnet_7.3-20                ##  [61] tidyselect_1.2.1            rstudioapi_0.17.1          ##  [63] dichromat_2.0-0.1           abind_1.4-8                ##  [65] yaml_2.3.10                 codetools_0.2-20           ##  [67] curl_7.0.0                  lattice_0.22-7             ##  [69] tibble_3.3.0                plyr_1.8.9                 ##  [71] withr_3.0.2                 Biobase_2.70.0             ##  [73] KEGGREST_1.50.0             S7_0.2.0                   ##  [75] evaluate_1.0.5              foreign_0.8-90             ##  [77] polyclip_1.10-7             Biostrings_2.78.0          ##  [79] pillar_1.11.1               BiocManager_1.30.26        ##  [81] MatrixGenerics_1.22.0       checkmate_2.3.3            ##  [83] stats4_4.5.1                OrganismDbi_1.52.0         ##  [85] generics_0.1.4              RCurl_1.98-1.17            ##  [87] ensembldb_2.34.0            S4Vectors_0.48.0           ##  [89] ggplot2_4.0.0               scales_1.4.0               ##  [91] ggbio_1.58.0                glue_1.8.0                 ##  [93] Hmisc_5.2-4                 lazyeval_0.2.2             ##  [95] tools_4.5.1                 BiocIO_1.20.0              ##  [97] data.table_1.17.8           BSgenome_1.78.0            ##  [99] GenomicAlignments_1.46.0    XML_3.99-0.19              ## [101] grid_4.5.1                  tidyr_1.3.1                ## [103] AnnotationDbi_1.72.0        colorspace_2.1-2           ## [105] ggforce_0.5.0               restfulr_0.0.16            ## [107] htmlTable_2.4.3             Formula_1.2-5              ## [109] cli_3.6.5                   NbClust_3.0.1              ## [111] S4Arrays_1.10.0             AnnotationFilter_1.34.0    ## [113] gtable_0.3.6                sass_0.4.10                ## [115] digest_0.6.37               BiocGenerics_0.56.0        ## [117] SparseArray_1.10.0          rjson_0.2.23               ## [119] htmlwidgets_1.6.4           farver_2.1.2               ## [121] memoise_2.0.1               htmltools_0.5.8.1          ## [123] lifecycle_1.0.4             httr_1.4.7                 ## [125] MASS_7.3-65                 bit64_4.6.0-1

Reference