Hi guys,

Im looking for some specific help with the Gviz package and its ability to plot bed files with many features. Id like to colour each feature in an epigenomics roadmap 15 state chromHMM bed file for a figure im preparing but I can't seem to group the features to plot each colour (Rgb code is a column in the GRange object) on an AnnotationTrack. 

Here's some of the GRange object:

GRanges object with 11583 ranges and 4 metadata columns:
          seqnames                 ranges strand |        name     score     itemRgb
             <Rle>              <IRanges>  <Rle> | <character> <numeric> <character>
      [1]     chr3     [3151401, 3152200]      * |      1_TssA         0     #FF0000
      [2]     chr3     [3152201, 3152600]      * |       7_Enh         0     #FFFF00
      [3]     chr3     [3167601, 3168000]      * |       7_Enh         0     #FFFF00
      [4]     chr3     [3168001, 3168400]      * |  2_TssAFlnk         0     #FF4500
      [5]     chr3     [3168401, 3169400]      * |      1_TssA         0     #FF0000

I did notice a question answered thats fairly close to what im after, but unfortunately its dealing with the UCSCtrack functionality and downloaded tables (https://support.bioconductor.org/p/50192/). Unfortunately UCSC dont have the samples I need. Ive been reading up on how to change displayParams but im getting no-where fast

So far I've tried:

hmmTrack <- AnnotationTrack(Tcell_effmem_pblood, start = from,  end = to, chromosome = "chr3", id = Tcell_effmem_pblood$name, width = 10, genome="hg19", stacking = "dense", feature = Tcell_effmem_pblood$itemRgb, name = "Tcell effmem")
feat <- unique(feature(hmmTrack))
featCol <- setNames(as.list(rgb(t(sapply(strsplit(feat, " "), as.numeric)), maxColorValue=255)), feat)displayPars(hmmTrack) <- featCol
displayPars(hmmTrack) <- featCol

Which gives me the error:

> feat <- unique(feature(hmmTrack))
> featCol <- setNames(as.list(rgb(t(sapply(strsplit(feat, " "),
+                                          as.numeric)), maxColorValue=255)), feat)
Error in rgb(t(sapply(strsplit(feat, " "), as.numeric)), maxColorValue = 255) : 
  color intensity NA, not in 0:255
In addition: Warning messages:
1: In lapply(X = X, FUN = FUN, ...) : NAs introduced by coercion
2: In lapply(X = X, FUN = FUN, ...) : NAs introduced by coercion
3: In lapply(X = X, FUN = FUN, ...) : NAs introduced by coercion
4: In lapply(X = X, FUN = FUN, ...) : NAs introduced by coercion
5: In lapply(X = X, FUN = FUN, ...) : NAs introduced by coercion
6: In lapply(X = X, FUN = FUN, ...) : NAs introduced by coercion
7: In lapply(X = X, FUN = FUN, ...) : NAs introduced by coercion

Any help would be much appreciated.

Cheers,

JB

> sessionInfo()
R version 3.3.1 (2016-06-21)
Platform: x86_64-apple-darwin16.0.0 (64-bit)
Running under: OS X 10.12.1 (Sierra)

locale:
[1] en_AU.UTF-8/en_AU.UTF-8/en_AU.UTF-8/C/en_AU.UTF-8/en_AU.UTF-8

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

other attached packages:
 [1] coMET_1.6.0                             trackViewer_1.10.0                     
 [3] ggbio_1.22.0                            psych_1.6.9                            
 [5] biomaRt_2.30.0                          BiocInstaller_1.24.0                   
 [7] chromophobe_0.95                        fastcluster_1.1.21                     
 [9] reshape2_1.4.2                          devtools_1.12.0                        
[11] R.4Cker_0.0.0.9000                      TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2
[13] GenomicFeatures_1.26.0                  AnnotationDbi_1.36.0                   
[15] Biobase_2.34.0                          Gviz_1.18.0                            
[17] rtracklayer_1.34.1                      GenomicRanges_1.26.1                   
[19] GenomeInfoDb_1.10.1                     IRanges_2.8.1                          
[21] S4Vectors_0.12.0                        BiocGenerics_0.20.0                    
[23] pheatmap_1.0.8                          ggplot2_2.1.0                          

loaded via a namespace (and not attached):
 [1] bitops_1.0-6                  matrixStats_0.51.0            RColorBrewer_1.1-2           
 [4] httr_1.2.1                    tools_3.3.1                   R6_2.2.0                     
 [7] rpart_4.1-10                  Hmisc_4.0-0                   DBI_0.5-1                    
[10] colorspace_1.3-0              nnet_7.3-12                   withr_1.0.2                  
[13] gridExtra_2.2.1               GGally_1.2.0                  mnormt_1.5-5                 
[16] DESeq2_1.14.0                 curl_2.2                      git2r_0.15.0                 
[19] chron_2.3-47                  graph_1.52.0                  htmlTable_1.7                
[22] grImport_0.9-0                scales_0.4.1                  genefilter_1.56.0            
[25] pbapply_1.3-1                 RBGL_1.50.0                   stringr_1.1.0                
[28] digest_0.6.10                 Rsamtools_1.26.1              foreign_0.8-67               
[31] XVector_0.14.0                dichromat_2.0-0               htmltools_0.3.5              
[34] ensembldb_1.6.0               BSgenome_1.42.0               RSQLite_1.0.0                
[37] shiny_0.14.2                  BiocParallel_1.8.1            acepack_1.4.1                
[40] VariantAnnotation_1.20.0      RCurl_1.95-4.8                magrittr_1.5                 
[43] Formula_1.2-1                 Matrix_1.2-7.1                Rcpp_0.12.7                  
[46] munsell_0.4.3                 stringi_1.1.2                 MASS_7.3-45                  
[49] SummarizedExperiment_1.4.0    zlibbioc_1.20.0               plyr_1.8.4                   
[52] AnnotationHub_2.6.0           lattice_0.20-34               Biostrings_2.42.0            
[55] splines_3.3.1                 hash_2.2.6                    annotate_1.52.0              
[58] locfit_1.5-9.1                knitr_1.15                    geneplotter_1.52.0           
[61] XML_3.98-1.5                  biovizBase_1.22.0             latticeExtra_0.6-28          
[64] data.table_1.9.6              httpuv_1.3.3                  miscTools_0.6-16             
[67] gtable_0.2.0                  reshape_0.8.6                 mime_0.5                     
[70] xtable_1.8-2                  depmixS4_1.3-3                colortools_0.1.5             
[73] Rsolnp_1.16                   survival_2.40-1               truncnorm_1.0-7              
[76] OrganismDbi_1.16.0            GenomicAlignments_1.10.0      memoise_1.0.0                
[79] corrplot_0.77                 cluster_2.0.5                 interactiveDisplayBase_1.12.0

Hi,

I can produce a colored plot  annotationTrack above:

Tcell_effmem_pblood <- data.frame(seqnames = c("chr3", "chr3", "chr3", "chr3", "chr3"),
           start = c(3151401L, 3152201L, 3167601L, 3168001L, 3168401L),
           end = c(3152200L, 3152600L, 3168000L, 3168400L, 3169400L), 
           strand = c("*", "*", "*", "*", "*"),
           name = c("1_TssA", "7_Enh", "7_Enh", "2_TssAFlnk", "1_TssA"),
           score = c(0L, 0L, 0L, 0L, 0L),
           itemRgb = c("#FF0000", "#FFFF00", "#FFFF00", "#FF4500", "#FF0000"))
Tcell_effmem_pblood <- as(Tcell_effmem_pblood, "GRanges")

hmmTrack <- AnnotationTrack(Tcell_effmem_pblood, start = from,  end = to, chromosome = "chr3", id = Tcell_effmem_pblood$name, width = 10, genome="hg19", stacking = "dense", feature = Tcell_effmem_pblood$itemRgb, name = "Tcell effmem")

plotTracks(hmmTrack, groupAnnotation="feature", "#FF0000"="#FF0000", "#FFFF00"="#FFFF00", "#FF4500"="#FF4500")

Is that what do you want to achieve?

Best

Robert

Hi,

In my r package coMET, I allow user to visualise chrommHMM using Roadmap color or our color

https://bioconductor.org/packages/release/bioc/html/coMET.html, you have different color sets described in the vignette.  This was implemented in the function "chromHMM_RoadMap". Feel free to use it and if you have questions, feel free to ask . I wrapped other data with also some options for the colors.

Regards,

Tiphaine  

Hi,

did you manage to solve this problem ?

Hi Robert,

I did the same thing but still not working.

y <- import.bed("chromatin_stats.bed")

y

GRanges object with 13627678 ranges and 4 metadata columns:
             seqnames               ranges strand |        name     score     itemRgb                thick
                <Rle>            <IRanges>  <Rle> | <character> <numeric> <character>            <IRanges>
         [1]     chr1          [  1,  200]      * |       Quies       999     #DCDCDC          [  1,  200]
         [2]     chr1          [201,  400]      * |       Quies       999     #DCDCDC          [201,  400]
         [3]     chr1          [401,  600]      * |       Quies       998     #DCDCDC          [401,  600]
         [4]     chr1          [601,  800]      * |       Quies       998     #DCDCDC          [601,  800]
         [5]     chr1          [801, 1000]      * |       Quies       998     #DCDCDC          [801, 1000]
         ...      ...                  ...    ... .         ...       ...         ...                  ...
  [13627674]     chrY [91743601, 91743800]      * |       Quies       984     #DCDCDC [91743601, 91743800]
  [13627675]     chrY [91743801, 91744000]      * |       Quies       983     #DCDCDC [91743801, 91744000]
  [13627676]     chrY [91744001, 91744200]      * |       Quies       981     #DCDCDC [91744001, 91744200]
  [13627677]     chrY [91744201, 91744400]      * |       Quies       979     #DCDCDC [91744201, 91744400]
  [13627678]     chrY [91744401, 91744600]      * |       Quies       975     #DCDCDC [91744401, 91744600]
  -------
  seqinfo: 22 sequences from an unspecified genome; no seqlengths​

hmmTrack <- AnnotationTrack(y , start = from,  end = to, chromosome = chr, id = y$name, width = 10, genome= gen, stacking = "dense", feature = y$itemRgb, name = "chromHMM")

plotTracks(hmmTrack​)

but I am still missing the color code of my bed track