Hi,
First thanks for your effort in the Signac package.
I use the function BigwigTrack to visualize .bigwig files and it worked very well in 1.5.0.
I just undated to 1.6.0, and found that not working even with the same code on the same file.
plot <- BigwigTrack(StringToGRanges('chr11-120970001-120980000'),'file.bigwig',smooth = 200,type = "coverage",y_label = "bigWig",max.downsample = 3000,downsample.rate = 0.1)
Here is the error message:
Error in data.frame(position = start(x = region):end(x = region), score = region_data, :
arguments imply differing number of rows: 10000, 0
I tried different files, and the error persists with version 1.6.0.
I also tried another computer with version 1.5.0, then it works.
I tried to understand what is wrong, and it seems that something wrong when trying to build a data frame from .bw file.
https://stackoverflow.com/questions/26147558/what-does-the-error-arguments-imply-differing-number-of-rows-x-y-mean
Could you help figure out what happened?
Thanks
sessionInfo()
R version 4.1.2 (2021-11-01)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Catalina 10.15.7
Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRlapack.dylib
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] Signac_1.6.0
loaded via a namespace (and not attached):
[1] fastmatch_1.1-3 plyr_1.8.6 igraph_1.2.10
[4] lazyeval_0.2.2 splines_4.1.2 BiocParallel_1.28.3
[7] listenv_0.8.0 scattermore_0.7 SnowballC_0.7.0
[10] GenomeInfoDb_1.30.0 ggplot2_3.3.5 digest_0.6.29
[13] htmltools_0.5.2 fansi_0.5.0 magrittr_2.0.1
[16] tensor_1.5 cluster_2.1.2 ROCR_1.0-11
[19] globals_0.14.0 Biostrings_2.62.0 matrixStats_0.61.0
[22] docopt_0.7.1 spatstat.sparse_2.1-0 colorspace_2.0-2
[25] ggrepel_0.9.1 dplyr_1.0.7 sparsesvd_0.2
[28] crayon_1.4.2 RCurl_1.98-1.5 jsonlite_1.7.2
[31] spatstat.data_2.1-2 survival_3.2-13 zoo_1.8-9
[34] glue_1.6.0 polyclip_1.10-0 gtable_0.3.0
[37] zlibbioc_1.40.0 XVector_0.34.0 leiden_0.3.9
[40] DelayedArray_0.20.0 future.apply_1.8.1 BiocGenerics_0.40.0
[43] abind_1.4-5 scales_1.1.1 DBI_1.1.2
[46] miniUI_0.1.1.1 Rcpp_1.0.7 viridisLite_0.4.0
[49] xtable_1.8-4 reticulate_1.22 spatstat.core_2.3-2
[52] stats4_4.1.2 htmlwidgets_1.5.4 httr_1.4.2
[55] RColorBrewer_1.1-2 ellipsis_0.3.2 Seurat_4.1.0
[58] ica_1.0-2 pkgconfig_2.0.3 XML_3.99-0.8
[61] farver_2.1.0 ggseqlogo_0.1 uwot_0.1.11
[64] deldir_1.0-6 utf8_1.2.2 tidyselect_1.1.1
[67] rlang_0.4.12 reshape2_1.4.4 later_1.3.0
[70] munsell_0.5.0 tools_4.1.2 generics_0.1.1
[73] ggridges_0.5.3 stringr_1.4.0 fastmap_1.1.0
[76] yaml_2.2.1 goftest_1.2-3 fitdistrplus_1.1-6
[79] purrr_0.3.4 RANN_2.6.1 pbapply_1.5-0
[82] future_1.23.0 nlme_3.1-153 mime_0.12
[85] slam_0.1-49 RcppRoll_0.3.0 compiler_4.1.2
[88] rstudioapi_0.13 plotly_4.10.0 png_0.1-7
[91] spatstat.utils_2.3-0 tibble_3.1.6 tweenr_1.0.2
[94] stringi_1.7.6 lattice_0.20-45 Matrix_1.4-0
[97] vctrs_0.3.8 pillar_1.6.4 lifecycle_1.0.1
[100] spatstat.geom_2.3-1 lmtest_0.9-39 RcppAnnoy_0.0.19
[103] data.table_1.14.2 cowplot_1.1.1 bitops_1.0-7
[106] irlba_2.3.5 httpuv_1.6.4 patchwork_1.1.1
[109] rtracklayer_1.54.0 GenomicRanges_1.46.1 R6_2.5.1
[112] BiocIO_1.4.0 promises_1.2.0.1 KernSmooth_2.23-20
[115] gridExtra_2.3 lsa_0.73.2 IRanges_2.28.0
[118] parallelly_1.30.0 codetools_0.2-18 MASS_7.3-54
[121] assertthat_0.2.1 SummarizedExperiment_1.24.0 rjson_0.2.20
[124] SeuratObject_4.0.4 GenomicAlignments_1.30.0 qlcMatrix_0.9.7
[127] sctransform_0.3.3 Rsamtools_2.10.0 S4Vectors_0.32.3
[130] GenomeInfoDbData_1.2.7 mgcv_1.8-38 parallel_4.1.2
[133] grid_4.1.2 rpart_4.1-15 tidyr_1.1.4
[136] MatrixGenerics_1.6.0 Rtsne_0.15 ggforce_0.3.3
[139] Biobase_2.54.0 shiny_1.7.1 restfulr_0.0.13
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