Hi

I want to make a GRangesList containing exon,intron, promoter and TSS  that I can subsequently use with the genomation::annotateWithGeneParts function. Should be easy, however when I try do that starting from a GenomicFeatures txdb package, extracting the parts I want and then try to make `GRangeList` I get the ERROR:

Error in combine_CompressedList_objects(class(x), objects, use.names = FALSE,  :
  the objects to combine must be CompressedList objects (or NULLs)

Any help about how to solve this / what I am doing wrong is much appreciated :)

Thanks, Fabian

Reproducible example:

library(GenomicRanges)
library(TxDb.Hsapiens.UCSC.hg19.knownGene)
txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene

## needs to have 2 meta columns: score, name
exo <- exonicParts(txdb, linked.to.single.gene.only=TRUE)
mcols(exo) <- DataFrame("score" = exo$exon_rank,
                        "name" = exo$gene_id)
int <- intronicParts(txdb, linked.to.single.gene.only=TRUE)
mcols(int) <-  DataFrame("score" = rep(0, length(int$gene_id)),
                         "name" = int$gene_id)
grl <- GRangesList(exons=exo,introns=int)

sessionInfo()
R version 3.4.1 (2017-06-30)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS release 6.9 (Final)

Matrix products: default
BLAS: /mnt/various/local/genome/packages/R/3.4.1/lib64/R/lib/libRblas.so
LAPACK: /mnt/various/local/genome/packages/R/3.4.1/lib64/R/lib/libRlapack.so

locale:
 [1] LC_CTYPE=en_US.utf8       LC_NUMERIC=C             
 [3] LC_TIME=en_US.utf8        LC_COLLATE=en_US.utf8    
 [5] LC_MONETARY=en_US.utf8    LC_MESSAGES=en_US.utf8   
 [7] LC_PAPER=en_US.utf8       LC_NAME=C                
 [9] LC_ADDRESS=C              LC_TELEPHONE=C           
[11] LC_MEASUREMENT=en_US.utf8 LC_IDENTIFICATION=C      

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

other attached packages:
[1] TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2
[2] GenomicFeatures_1.28.5                 
[3] AnnotationDbi_1.38.2                   
[4] Biobase_2.36.2                         
[5] GenomicRanges_1.28.6                   
[6] GenomeInfoDb_1.12.3                    
[7] IRanges_2.10.5                         
[8] S4Vectors_0.14.7                       
[9] BiocGenerics_0.22.1                    

loaded via a namespace (and not attached):
 [1] Rcpp_0.12.13               XVector_0.16.0            
 [3] GenomicAlignments_1.12.2   zlibbioc_1.22.0           
 [5] BiocParallel_1.10.1        bit_1.1-12                
 [7] lattice_0.20-35            rlang_0.1.4               
 [9] blob_1.1.0                 tools_3.4.1               
[11] grid_3.4.1                 SummarizedExperiment_1.6.5
[13] DBI_0.7                    matrixStats_0.52.2        
[15] bit64_0.9-7                digest_0.6.12             
[17] tibble_1.3.4               Matrix_1.2-10             
[19] GenomeInfoDbData_0.99.0    rtracklayer_1.36.6        
[21] bitops_1.0-6               RCurl_1.95-4.8            
[23] biomaRt_2.32.1             memoise_1.1.0             
[25] RSQLite_2.0                DelayedArray_0.2.7        
[27] compiler_3.4.1             Rsamtools_1.28.0          
[29] Biostrings_2.44.2          XML_3.98-1.9              
[31] pkgconfig_2.0.1          

I would suggest first asking the genomation authors to provide a convenient coercion method from TxDb to whatever they expect. Or, there methods could just accept a TxDb as input.

To answer this question though, the problem is that the "score" column is an IntegerList in the exo object, but an integer vector in the int object. You can just cast the vector with IntegerList(), like:

mcols(int) <-  DataFrame("score" = IntegerList(rep(0, length(int$gene_id))),
                         "name" = int$gene_id)

Also, it looks like you are using some undocumented entry points into GenomicFeatures. I'd recommend using documented entry points like exons() and intronsForTranscripts() instead.

Thanks for the quick response Michael !

I agree that genomation should ideally accept txdb objects as input. Had to make a minor modification to make it work:

mcols(int) <- DataFrame("score" = as(rep(0, length(int)), "IntegerList"),
                        "name" = int$gene_id)

cheers, Fabian