Hi,
I am trying to put Gviz output and a basic R plot on the same canvas.
The figures I have:
1) A basic R plot recorded with recordPlot()
2) A bunch of Gviz tracks
Attempts I took:
I tried to grab the Gviz output using grid::grid.grabExp() and use cowplot::plot_grid() to put them on the same canvas.
tp <- grid.grabExpr(plotTracks(list(gtrack,ht),from = chrstart, to=chrend, chromosome = chrm, add = TRUE)) # >Warning message: # >In grabDL(warn, wrap, ...) : # >one of more grobs overwritten (grab WILL not be faithful; try 'wrap = TRUE') figure <- plot_grid(basic_R, tp)
The final figure did no 100% replicate what I saw with plotTracks(). Some (NOT ALL!) data tracks in "polygon" style lost their color fill in mountains. I could still see the colored line but the fill between colored peaks and baseline was totally lost.
Adding the 'wrap = TRUE' would not solve this problem and the error still occured.
How could I properly arrange them on the same canvas?
Thank you so much for your help!
SessionInfo:
R version 3.4.4 (2018-03-15) Platform: x86_64-pc-linux-gnu (64-bit) Running under: Ubuntu 14.04.5 LTS Matrix products: default BLAS: /usr/lib/libblas/libblas.so.3.0 LAPACK: /usr/lib/lapack/liblapack.so.3.0 locale: [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_SG.UTF-8 LC_COLLATE=en_US.UTF-8 LC_MONETARY=en_SG.UTF-8 [6] LC_MESSAGES=en_US.UTF-8 LC_PAPER=en_SG.UTF-8 LC_NAME=C LC_ADDRESS=C LC_TELEPHONE=C [11] LC_MEASUREMENT=en_SG.UTF-8 LC_IDENTIFICATION=C attached base packages: [1] parallel stats4 grid stats graphics grDevices utils datasets methods base other attached packages: [1] gridGraphics_0.3-0 gdtools_0.1.7 bindrcpp_0.2 [4] org.Hs.eg.db_3.5.0 TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2 GenomicFeatures_1.30.3 [7] AnnotationDbi_1.40.0 Biobase_2.38.0 Gviz_1.22.3 [10] GenomicRanges_1.30.3 GenomeInfoDb_1.14.0 IRanges_2.12.0 [13] S4Vectors_0.16.0 BiocGenerics_0.24.0 optparse_1.4.4 [16] Sushi_1.16.0 biomaRt_2.34.2 zoo_1.8-1 [19] forcats_0.3.0 stringr_1.3.0 tidyr_0.8.0 [22] tibble_1.4.2 tidyverse_1.2.1 RColorBrewer_1.1-2 [25] cowplot_0.9.2 gridExtra_2.3 ggpubr_0.1.6.999 [28] magrittr_1.5 svglite_1.2.1 scales_0.5.0.9000 [31] ggrepel_0.7.3 ggplot2_2.2.1.9000 purrr_0.2.4 [34] readr_1.1.1 dplyr_0.7.4 here_0.1 loaded via a namespace (and not attached): [1] colorspace_1.3-2 rprojroot_1.3-2 biovizBase_1.26.0 htmlTable_1.11.2 [5] XVector_0.18.0 base64enc_0.1-3 dichromat_2.0-0 rstudioapi_0.7 [9] getopt_1.20.2 bit64_0.9-7 interactiveDisplayBase_1.16.0 lubridate_1.7.4 [13] xml2_1.2.0 splines_3.4.4 mnormt_1.5-5 knitr_1.20 [17] Formula_1.2-2 jsonlite_1.5 Rsamtools_1.30.0 broom_0.4.3 [21] cluster_2.0.7-1 shiny_1.0.5 compiler_3.4.4 httr_1.3.1 [25] backports_1.1.2 assertthat_0.2.0 Matrix_1.2-14 lazyeval_0.2.1 [29] cli_1.0.0 acepack_1.4.1 htmltools_0.3.6 prettyunits_1.0.2 [33] tools_3.4.4 gtable_0.2.0 glue_1.2.0 GenomeInfoDbData_1.0.0 [37] reshape2_1.4.3 Rcpp_0.12.16 cellranger_1.1.0 Biostrings_2.46.0 [41] nlme_3.1-137 rtracklayer_1.38.3 psych_1.7.8 rvest_0.3.2 [45] mime_0.5 ensembldb_2.2.2 XML_3.98-1.10 AnnotationHub_2.10.1 [49] zlibbioc_1.24.0 BSgenome_1.46.0 BiocInstaller_1.28.0 VariantAnnotation_1.24.5 [53] ProtGenerics_1.10.0 hms_0.4.2 SummarizedExperiment_1.8.1 AnnotationFilter_1.2.0 [57] curl_3.1 yaml_2.1.18 memoise_1.1.0 rpart_4.1-13 [61] latticeExtra_0.6-28 stringi_1.1.7 RSQLite_2.0 RMySQL_0.10.14 [65] checkmate_1.8.5 BiocParallel_1.12.0 rlang_0.2.0.9001 pkgconfig_2.0.1 [69] bitops_1.0-6 matrixStats_0.53.1 lattice_0.20-35 bindr_0.1.1 [73] labeling_0.3 GenomicAlignments_1.14.1 htmlwidgets_1.0 bit_1.1-12 [77] plyr_1.8.4 R6_2.2.2 Hmisc_4.1-1 DelayedArray_0.4.1 [81] DBI_0.8 pillar_1.2.2 haven_1.1.1 foreign_0.8-70 [85] withr_2.1.2 survival_2.42-3 RCurl_1.95-4.10 nnet_7.3-12 [89] modelr_0.1.1 crayon_1.3.4 progress_1.1.2 readxl_1.1.0 [93] data.table_1.10.4-3 blob_1.1.0 digest_0.6.15 xtable_1.8-2 [97] httpuv_1.3.6.2 munsell_0.4.3