DEXSeq: mcols(dxd)$fullBetaConv either contains TRUE or NA
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Last seen 6 months ago

If I run testForDEU(), the resulting DEXSeqDataSet object only contains TRUE or NA and no FALSE entries for mcols(dxd)$fullBetaConv. According to the summary stats, it seems that NA can be interpreted as FALSE. Is this a bug?

> sessionInfo()
R version 4.2.0 (2022-04-22)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Red Hat Enterprise Linux Server 7.9 (Maipo)

Matrix products: default
BLAS/LAPACK: /usr/lib64/

 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C               LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8     LC_MONETARY=en_US.UTF-8   
 [6] LC_MESSAGES=en_US.UTF-8    LC_PAPER=en_US.UTF-8       LC_NAME=C                  LC_ADDRESS=C               LC_TELEPHONE=C            

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

other attached packages:
 [1] RSQLite_2.2.14              stageR_1.18.0               rtracklayer_1.56.1          dplyr_1.0.9                 ArvadosR_2.4.0             
 [6] DEXSeq_1.42.0               RColorBrewer_1.1-3          AnnotationDbi_1.58.0        DESeq2_1.36.0               SummarizedExperiment_1.26.1
[11] GenomicRanges_1.48.0        GenomeInfoDb_1.32.2         IRanges_2.30.0              S4Vectors_0.34.0            MatrixGenerics_1.8.1       
[16] matrixStats_0.62.0          Biobase_2.56.0              BiocGenerics_0.42.0         BiocParallel_1.30.3        

loaded via a namespace (and not attached):
 [1] bitops_1.0-7             bit64_4.0.5              filelock_1.0.2           progress_1.2.2           httr_1.4.3               tools_4.2.0             
 [7] utf8_1.2.2               R6_2.5.1                 DBI_1.1.2                colorspace_2.0-3         tidyselect_1.1.2         prettyunits_1.1.1       
[13] bit_4.0.4                curl_4.3.2               compiler_4.2.0           cli_3.3.0                xml2_1.3.3               DelayedArray_0.22.0     
[19] scales_1.2.0             genefilter_1.78.0        rappdirs_0.3.3           stringr_1.4.0            digest_0.6.29            Rsamtools_2.12.0        
[25] XVector_0.36.0           pkgconfig_2.0.3          dbplyr_2.2.0             fastmap_1.1.0            rlang_1.0.2              rstudioapi_0.13         
[31] BiocIO_1.6.0             generics_0.1.2           hwriter_1.3.2.1          RCurl_1.98-1.7           magrittr_2.0.3           GenomeInfoDbData_1.2.8  
[37] Matrix_1.4-1             Rcpp_1.0.8.3             munsell_0.5.0            fansi_1.0.3              lifecycle_1.0.1          stringi_1.7.6           
[43] yaml_2.3.5               zlibbioc_1.42.0          BiocFileCache_2.4.0      grid_4.2.0               blob_1.2.3               parallel_4.2.0          
[49] crayon_1.5.1             lattice_0.20-45          Biostrings_2.64.0        splines_4.2.0            annotate_1.74.0          hms_1.1.1               
[55] KEGGREST_1.36.3          locfit_1.5-9.5           pillar_1.7.0             rjson_0.2.21             geneplotter_1.74.0       codetools_0.2-18        
[61] biomaRt_2.52.0           XML_3.99-0.10            glue_1.6.2               png_0.1-7                vctrs_0.4.1              gtable_0.3.0            
[67] purrr_0.3.4              assertthat_0.2.1         cachem_1.0.6             ggplot2_3.3.6            xtable_1.8-4             restfulr_0.0.15         
[73] survival_3.3-1           tibble_3.1.7             GenomicAlignments_1.32.0 memoise_2.0.1            statmod_1.4.36           ellipsis_0.3.2
DEXSeq • 404 views

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