Dear wavClusteR users,
I forged a custom BSgenome and I use wavClusteR to analyze PAR-CLIP clusters. I found that wavClusteR failed if I use the following options:
highConfSub <- getHighConfSub( countTable,
support = support,
substitution = "TC" )
head( highConfSub )
clusters <- getClusters( highConfSub = highConfSub,
coverage = coverage,
sortedBam = Bam,
threshold = 1,
cores = 4 )
clusters
require(BSgenome.RREWTM1TP356A.Xiao.NL43)
wavclusters <- filterClusters( clusters = clusters,
highConfSub = highConfSub,
coverage = coverage,
model = model,
genome = RREWT_M1T_P356A,
refBase = "T",
minWidth = 12)
wavclusters
Computing log odds...
Refining cluster sizes...
Combining clusters...
Quantifying transitions within clusters...
Computing statistics...
Error in .Call2("C_solve_user_SEW", refwidths, start, end, width, translate.negative.coord, : solving row 1: the supplied start/end lead to a negative width
I found that I have to use specific user-defined parameters for the highConfSub function for wavclusters to work.
highConfSub <- getHighConfSub( countTable,
supportStart = 0.2,
supportEnd = 0.8,
substitution = "TC" )
head( highConfSub )
clusters <- getClusters( highConfSub = highConfSub,
coverage = coverage,
sortedBam = Bam,
threshold = 1,
cores = 4 )
clusters
require(BSgenome.RREWTM1TP356A.Xiao.NL43)
wavclusters <- filterClusters( clusters = clusters,
highConfSub = highConfSub,
coverage = coverage,
model = model,
genome = RREWT_M1T_P356A,
refBase = "T",
minWidth = 12)
wavclusters
Computing log odds...
Refining cluster sizes...
Combining clusters...
Quantifying transitions within clusters...
Computing statistics...
|==============================================================================================================================| 100%
Consolidating results...
However, if I use supportStart = 0.1, supportEnd = 0.9 in highConfSub, wavclusters would fail again with the same error (Error in .Call2("C_solve_user_SEW", refwidths, start, end, width, translate.negative.coord, : solving row 1: the supplied start/end lead to a negative width).
This problem is really perplexing and I wonder if anyone has similar problems and would like to give some inputs on this.
Thanks,
Xiao
Session Info:
R version 4.1.1 (2021-08-10) Platform: x86_64-apple-darwin17.0 (64-bit) Running under: macOS Mojave 10.14.6
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] parallel stats4 stats graphics grDevices utils datasets methods base
other attached packages:
[1] BSgenome.RREWTM1TP356A.Xiao.NL43_0.1 BSgenome.RREWTCLIP.Xiao.NL43_0.1 BSgenome.Hsapiens.UCSC.hg19_1.4.3
[4] BiocManager_1.30.16 BSgenome_1.60.0 rtracklayer_1.52.1
[7] wavClusteR_2.26.0 Rsamtools_2.8.0 Biostrings_2.60.2
[10] XVector_0.32.0 GenomicRanges_1.44.0 GenomeInfoDb_1.28.4
[13] IRanges_2.26.0 S4Vectors_0.30.0 BiocGenerics_0.38.0
loaded via a namespace (and not attached):
[1] bitops_1.0-7 matrixStats_0.60.1 bit64_4.0.5 filelock_1.0.2
[5] RColorBrewer_1.1-2 progress_1.2.2 httr_1.4.2 backports_1.2.1
[9] tools_4.1.1 utf8_1.2.2 R6_2.5.1 rpart_4.1-15
[13] Hmisc_4.5-0 DBI_1.1.1 colorspace_2.0-2 ade4_1.7-17
[17] nnet_7.3-16 tidyselect_1.1.1 gridExtra_2.3 prettyunits_1.1.1
[21] bit_4.0.4 curl_4.3.2 compiler_4.1.1 Biobase_2.52.0
[25] htmlTable_2.2.1 xml2_1.3.2 DelayedArray_0.18.0 checkmate_2.0.0
[29] scales_1.1.1 rappdirs_0.3.3 stringr_1.4.0 digest_0.6.27
[33] foreign_0.8-81 htmltools_0.5.2 base64enc_0.1-3 jpeg_0.1-9
[37] pkgconfig_2.0.3 MatrixGenerics_1.4.3 dbplyr_2.1.1 fastmap_1.1.0
[41] htmlwidgets_1.5.4 rlang_0.4.11 rstudioapi_0.13 RSQLite_2.2.8
[45] BiocIO_1.2.0 generics_0.1.0 mclust_5.4.7 BiocParallel_1.26.2
[49] dplyr_1.0.7 RCurl_1.98-1.4 magrittr_2.0.1 GenomeInfoDbData_1.2.6
[53] Formula_1.2-4 Matrix_1.3-4 Rcpp_1.0.7 munsell_0.5.0
[57] fansi_0.5.0 lifecycle_1.0.0 stringi_1.7.4 yaml_2.2.1
[61] MASS_7.3-54 SummarizedExperiment_1.22.0 zlibbioc_1.38.0 BiocFileCache_2.0.0
[65] grid_4.1.1 blob_1.2.2 crayon_1.4.1 lattice_0.20-44
[69] splines_4.1.1 GenomicFeatures_1.44.2 hms_1.1.0 KEGGREST_1.32.0
[73] knitr_1.34 pillar_1.6.2 rjson_0.2.20 seqinr_4.2-8
[77] codetools_0.2-18 biomaRt_2.48.3 XML_3.99-0.7 glue_1.4.2
[81] latticeExtra_0.6-29 data.table_1.14.0 png_0.1-7 vctrs_0.3.8
[85] foreach_1.5.1 gtable_0.3.0 purrr_0.3.4 assertthat_0.2.1
[89] cachem_1.0.6 ggplot2_3.3.5 xfun_0.26 restfulr_0.0.13
[93] survival_3.2-13 tibble_3.1.4 iterators_1.0.13 GenomicAlignments_1.28.0
[97] AnnotationDbi_1.54.1 memoise_2.0.0 cluster_2.1.2 ellipsis_0.3.2
