Question: Cannot specify groups when overlaying aligned read tracks
gravatar for JohnTownsend
6 months ago by
JohnTownsend20 wrote:

I am trying to overlay two sets of read depth data on a single track in Gviz. As a minimal example, I can get this data plotted on two tracks:


coords <- seq(from=1000, to=5000, by=100)

starts1 <- sample(1500:4500, 10)
ends1 <- starts1 + 100
reads1 <- GRanges(Rle("chr1"), IRanges(starts1, ends1), strand = Rle("+"))

starts2 <- sample(1500:4500, 10)
ends2 <- starts2 + 100
reads2 <- GRanges(Rle("chr1"), IRanges(starts2, ends2), strand = Rle("+"))

ax <- GenomeAxisTrack()

T1 <- AlignedReadTrack(reads1)
T2 <- AlignedReadTrack(reads2)

plotTracks(list(ax, T1, T2))

I can also overlay these two tracks

ot <- OverlayTrack(list(T1, T2))

plotTracks(list(ax, ot))

However, this is not very useful as I cannot distinguish between the two datasets. So I've tried to specify each track as a separate group before overlaying them.

T1 <- AlignedReadTrack(reads1, groups = factor("sample 1", levels = c("sample 1", "sample 2")), legend = TRUE)
T2 <- AlignedReadTrack(reads2, groups = factor("sample 2", levels = c("sample 1", "sample 2")), legend = TRUE)

ot <- OverlayTrack(list(T1, T2))

plotTracks(list(ax, ot))

But this gives me the following error:

Error in rep(yy, nrow(valsS)) : invalid 'times' argument

Am I making a mistake somewhere? Or is this because the AlignedReadTrack is still in development, so there are still bugs like this coming up?

Many thanks!


PS. Here's my sessionInfo()

R version 3.4.2 (2017-09-28)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: OS X El Capitan 10.11.6

Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRlapack.dylib

[1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8

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

other attached packages:
[1] Gviz_1.20.0          GenomicRanges_1.28.3 GenomeInfoDb_1.12.1  IRanges_2.10.2      
[5] S4Vectors_0.14.7     BiocGenerics_0.22.0

loaded via a namespace (and not attached):
 [1] Biobase_2.36.2                httr_1.2.1                    bit64_0.9-7                  
 [4] AnnotationHub_2.8.2           splines_3.4.2                 shiny_1.0.3                  
 [7] Formula_1.2-2                 interactiveDisplayBase_1.14.0 latticeExtra_0.6-28          
[10] blob_1.1.0                    BSgenome_1.44.0               GenomeInfoDbData_0.99.0      
[13] Rsamtools_1.28.0              yaml_2.1.14                   RSQLite_2.0                  
[16] backports_1.1.0               lattice_0.20-35               biovizBase_1.24.0            
[19] digest_0.6.12                 RColorBrewer_1.1-2            XVector_0.16.0               
[22] checkmate_1.8.3               colorspace_1.3-2              httpuv_1.3.3                 
[25] htmltools_0.3.6               Matrix_1.2-11                 plyr_1.8.4                   
[28] XML_3.98-1.7                  biomaRt_2.32.1                zlibbioc_1.22.0              
[31] xtable_1.8-2                  scales_0.4.1                  BiocParallel_1.10.1          
[34] htmlTable_1.9                 tibble_1.3.4                  AnnotationFilter_1.0.0       
[37] ggplot2_2.2.1                 SummarizedExperiment_1.6.3    GenomicFeatures_1.28.5       
[40] nnet_7.3-12                   lazyeval_0.2.0                mime_0.5                     
[43] survival_2.41-3               magrittr_1.5                  memoise_1.1.0                
[46] foreign_0.8-69                BiocInstaller_1.26.1          tools_3.4.2                  
[49] data.table_1.10.4             matrixStats_0.52.2            stringr_1.2.0                
[52] munsell_0.4.3                 cluster_2.0.6                 DelayedArray_0.2.7           
[55] AnnotationDbi_1.38.1          ensembldb_2.0.4               Biostrings_2.44.1            
[58] compiler_3.4.2                rlang_0.1.2.9000              RCurl_1.95-4.8               
[61] dichromat_2.0-0               VariantAnnotation_1.22.1      htmlwidgets_0.9              
[64] bitops_1.0-6                  base64enc_0.1-3               gtable_0.2.0                 
[67] curl_2.8.1                    DBI_0.6-1                     R6_2.2.2                     
[70] GenomicAlignments_1.12.2      gridExtra_2.2.1               knitr_1.16                   
[73] rtracklayer_1.36.3            bit_1.1-12                    Hmisc_4.0-3                  
[76] ProtGenerics_1.8.0            stringi_1.1.5                 Rcpp_0.12.13                 
[79] rpart_4.1-11                  acepack_1.4.1 
ADD COMMENTlink modified 6 months ago by Robert Ivanek520 • written 6 months ago by JohnTownsend20
gravatar for Robert Ivanek
6 months ago by
Robert Ivanek520
Robert Ivanek520 wrote:

Hi John,

You can either use annotation tracks and then code similar to this one should work:

T1 <- AnnotationTrack(reads1, feature = factor(rep("sample 1",length(reads1)), levels = c("sample 1", "sample 2")), shape = "box", showId=FALSE)
T2 <- AnnotationTrack(reads2, feature = factor(rep("sample 2",length(reads2)), levels = c("sample 1", "sample 2")), shape = "box", showId=FALSE)

ot <- OverlayTrack(list(T1, T2))

plotTracks(list(ax, ot), groupAnnotation = "feature", `sample 1` = "darkred", `sample 2` = "darkgreen")

Or if you want to show legend then you need to use DataTrack and then you can follow the example in the vignette (chapter 5.2 Overlays)

Hope that helps

ADD COMMENTlink written 6 months ago by Robert Ivanek520
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