Rqc crashes on Windows operating system

[CarmineFruggiero]

Using the "Main Rqc function", namely Rqc::rqc, the R session aborted.
My code was:

Rqc::rqc(
    path = ".", 
    pattern = ".fastq.gz", 
    openBrowser = FALSE, 
    sample = TRUE)

Input data are two compressed FASTQ files, available at:
ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR225/042/SRR22559142/SRR22559142_1.fastq.gz
ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR225/042/SRR22559142/SRR22559142_2.fastq.gz

session.info() output is the following:

R version 4.4.1 (2024-06-14 ucrt)
Platform: x86_64-w64-mingw32/x64
Running under: Windows 11 x64 (build 26100)

Matrix products: default

locale:
[1] LC_COLLATE=Italian_Italy.utf8 LC_CTYPE=Italian_Italy.utf8
[3] LC_MONETARY=Italian_Italy.utf8 LC_NUMERIC=C
[5] LC_TIME=Italian_Italy.utf8

time zone: Europe/Rome
tzcode source: internal

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

other attached packages:
[1] Rqc_1.40.0 ggplot2_3.5.1
[3] ShortRead_1.64.0 GenomicAlignments_1.42.0
[5] SummarizedExperiment_1.36.0 Biobase_2.66.0
[7] MatrixGenerics_1.18.1 matrixStats_1.5.0
[9] Rsamtools_2.22.0 GenomicRanges_1.58.0
[11] Biostrings_2.74.1 GenomeInfoDb_1.42.3
[13] XVector_0.46.0 IRanges_2.40.1
[15] S4Vectors_0.44.0 BiocGenerics_0.52.0
[17] BiocParallel_1.40.0

loaded via a namespace (and not attached):
[1] RColorBrewer_1.1-3 rstudioapi_0.16.0 jsonlite_1.8.8
[4] magrittr_2.0.3 GenomicFeatures_1.58.0 rmarkdown_2.27
[7] BiocIO_1.16.0 zlibbioc_1.52.0 vctrs_0.6.5
[10] memoise_2.0.1 RCurl_1.98-1.16 base64enc_0.1-3
[13] htmltools_0.5.8.1 S4Arrays_1.6.0 curl_5.2.1
[16] SparseArray_1.6.2 Formula_1.2-5 htmlwidgets_1.6.4
[19] plyr_1.8.9 cachem_1.1.0 mime_0.12
[22] lifecycle_1.0.4 pkgconfig_2.0.3 Matrix_1.7-0
[25] R6_2.5.1 fastmap_1.2.0 GenomeInfoDbData_1.2.13
[28] shiny_1.9.1 digest_0.6.36 colorspace_2.1-1
[31] AnnotationDbi_1.68.0 Hmisc_5.1-3 RSQLite_2.3.9
[34] hwriter_1.3.2.1 fansi_1.0.6 httr_1.4.7
[37] abind_1.4-5 compiler_4.4.1 bit64_4.0.5
[40] withr_3.0.1 htmlTable_2.4.3 backports_1.5.0
[43] DBI_1.2.3 DelayedArray_0.32.0 rjson_0.2.23
[46] tools_4.4.1 foreign_0.8-86 httpuv_1.6.15
[49] nnet_7.3-19 glue_1.7.0 restfulr_0.0.15
[52] promises_1.3.0 grid_4.4.1 checkmate_2.3.2
[55] cluster_2.1.6 reshape2_1.4.4 generics_0.1.3
[58] gtable_0.3.5 BSgenome_1.74.0 ensembldb_2.30.0
[61] data.table_1.15.4 utf8_1.2.4 pillar_1.9.0
[64] markdown_1.13 stringr_1.5.1 later_1.3.2
[67] dplyr_1.1.4 lattice_0.22-6 rtracklayer_1.66.0
[70] bit_4.0.5 deldir_2.0-4 biovizBase_1.54.0
[73] tidyselect_1.2.1 knitr_1.48 gridExtra_2.3
[76] ProtGenerics_1.38.0 xfun_0.51 stringi_1.8.4
[79] UCSC.utils_1.2.0 lazyeval_0.2.2 yaml_2.3.10
[82] evaluate_0.24.0 codetools_0.2-20 interp_1.1-6
[85] GenomicFiles_1.42.0 tibble_3.2.1 BiocManager_1.30.25
[88] cli_3.6.3 rpart_4.1.23 xtable_1.8-4
[91] munsell_0.5.1 dichromat_2.0-0.1 Rcpp_1.0.13
[94] png_0.1-8 XML_3.99-0.18 parallel_4.4.1
[97] blob_1.2.4 latticeExtra_0.6-30 jpeg_0.1-10
[100] AnnotationFilter_1.30.0 bitops_1.0-9 pwalign_1.2.0
[103] VariantAnnotation_1.52.0 scales_1.3.0 crayon_1.5.3
[106] BiocStyle_2.34.0 rlang_1.1.4 KEGGREST_1.46.0

Below, I also reported the image generated by Rstudio, after few seconds from the beginning of the analysis.