Unconfigured Ad

Collapse
X
Collapse
 
  • Page of 1
  • Filter
  • Time
  • Show
Clear All
new posts
Previous template Next
  • stephenhart
    Member
    • Sep 2011
    • 16
    #1

    gene tracking with cummerBund - persistent problem

    Hello. I'm having some difficulty with the makeGeneRegionTrack feature of cummerBund. If I rebuild my cuffData.db with 'mm10_ensGene.gtf', then the following happens:

    Code:
    > cuff <- readCufflinks(genome='mm10',gtfFile='mm10_ensGene.gtf',rebuild=TRUE)

> 	cuff
CuffSet instance with:
	 4 samples
	 23285 genes
	 30073 isoforms
	 25872 TSS
	 24748 CDS
	 139440 promoters
	 155232 splicing
	 122340 relCDS

> 	myGene
CuffGene instance for gene Insm2 
Short name:	 Insm2 
Slots:
	 annotation
	 features
	 fpkm
	 repFpkm
	 diff
	 count
	 isoforms	 CuffFeature instance of size 1 
	 TSS		 CuffFeature instance of size 1 
	 CDS		 CuffFeature instance of size 1 

> 	genetrack <- makeGeneRegionTrack(myGene)
Error in .Call2("Rle_constructor", values, lengths, check, 0L, PACKAGE = "IRanges") : 
  Rle of type 'list' is not supported
    On the other hand, if I rebuild my cuffData.db file with 'genes.gtf' from the Tuxedo package, then the following happens:



    Code:
    > cuff <- readCufflinks(genome='mm10',gtfFile='genes.gtf',rebuild=TRUE)

> 	cuff
CuffSet instance with:
	 4 samples
	 23285 genes
	 30073 isoforms
	 25872 TSS
	 24748 CDS
	 139440 promoters
	 155232 splicing
	 122340 relCDS

> 	myGene
CuffGene instance for gene Insm2 
Short name:	 Insm2 
Slots:
	 annotation
	 features
	 fpkm
	 repFpkm
	 diff
	 count
	 isoforms	 CuffFeature instance of size 1 
	 TSS		 CuffFeature instance of size 1 
	 CDS		 CuffFeature instance of size 1 

> 	genetrack <- makeGeneRegionTrack(myGene)
Error in `[.data.frame`(features(object), , featCols) : 
  undefined columns selected

    I've noticed similar problems in other posts, but with no solutions. Any suggestions would be appreciated.

    Thanks.
    Tags: cummerbund, gtf, rnaseq
  • axa9070
    Member
    • Oct 2014
    • 11
    #2
    stephenhart: I have the first issue but not that second one.

    Either way, does anyone have any ideas yet?


    Using EMBL annotation:
    Code:
    > cuff <- readCufflinks(genome="vinifera.fa", gtfFile="vinifera.gtf", rebuild=T)

>       cuff
CuffSet instance with:
         6 samples
         30446 genes
         32764 isoforms
         31480 TSS
         29927 CDS
         456690 promoters
         472200 splicing
         437595 relCDS

>       myGene
CuffGene instance for gene XLOC_001303
Short name:      SUT2
Slots:
         annotation
         features
         fpkm
         repFpkm
         diff
         count
         isoforms        CuffFeature instance of size 1
         TSS             CuffFeature instance of size 1
         CDS             CuffFeature instance of size 1
> genetrack <- makeGeneRegionTrack(myGene)
Error in .Call2("Rle_constructor", values, lengths, check, 0L, PACKAGE = "S4Vectors") :
  Rle of type 'list' is not supported

    Using my merged annotation:
    Code:
    > cuff <- readCufflinks(genome="vinifera.fa", gtfFile="merged.gtf", rebuild=T)

>       cuff
CuffSet instance with:
         6 samples
         30446 genes
         32764 isoforms
         31480 TSS
         29927 CDS
         456690 promoters
         472200 splicing
         437595 relCDS

>       myGene
CuffGene instance for gene XLOC_001303
Short name:      SUT2
Slots:
         annotation
         features
         fpkm
         repFpkm
         diff
         count
         isoforms        CuffFeature instance of size 1
         TSS             CuffFeature instance of size 1
         CDS             CuffFeature instance of size 1
> genetrack <- makeGeneRegionTrack(myGene)
Error in .Call2("Rle_constructor", values, lengths, check, 0L, PACKAGE = "S4Vectors") :
  Rle of type 'list' is not supported
    Here's my sessionInfo:
    Code:
    > sessionInfo()
R version 3.1.1 (2014-07-10)
Platform: x86_64-unknown-linux-gnu (64-bit)

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C
 [9] LC_ADDRESS=C               LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C

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

other attached packages:
 [1] cummeRbund_2.8.0     Gviz_1.10.2          rtracklayer_1.26.1
 [4] GenomicRanges_1.18.1 GenomeInfoDb_1.2.2   IRanges_2.0.0
 [7] S4Vectors_0.4.0      fastcluster_1.1.13   reshape2_1.4
[10] ggplot2_1.0.0        RSQLite_1.0.0        DBI_0.3.1
[13] BiocGenerics_0.12.0

loaded via a namespace (and not attached):
 [1] acepack_1.3-3.3          AnnotationDbi_1.28.1     base64enc_0.1-2
 [4] BatchJobs_1.5            BBmisc_1.8               Biobase_2.26.0
 [7] BiocParallel_1.0.0       biomaRt_2.22.0           Biostrings_2.34.0
[10] biovizBase_1.14.0        bitops_1.0-6             brew_1.0-6
[13] BSgenome_1.34.0          checkmate_1.5.0          cluster_1.15.3
[16] codetools_0.2-9          colorspace_1.2-4         dichromat_2.0-0
[19] digest_0.6.4             fail_1.2                 foreach_1.4.2
[22] foreign_0.8-61           Formula_1.1-2            GenomicAlignments_1.2.0
[25] GenomicFeatures_1.18.2   gtable_0.1.2             Hmisc_3.14-5
[28] iterators_1.0.7          lattice_0.20-29          latticeExtra_0.6-26
[31] MASS_7.3-35              matrixStats_0.10.3       munsell_0.4.2
[34] nnet_7.3-8               plyr_1.8.1               proto_0.3-10
[37] RColorBrewer_1.0-5       Rcpp_0.11.3              RCurl_1.95-4.3
[40] R.methodsS3_1.6.1        rpart_4.1-8              Rsamtools_1.18.1
[43] scales_0.2.4             sendmailR_1.2-1          splines_3.1.1
[46] stringr_0.6.2            survival_2.37-7          tools_3.1.1
[49] VariantAnnotation_1.12.2 XML_3.98-1.1             XVector_0.6.0
[52] zlibbioc_1.12.0

    Comment

    • axa9070
      Member
      • Oct 2014
      • 11
      #3
      hey stephenhart:
      Would you mind posting this function's output:

      Code:
      > head(features(myGene))
  seqnames    start      end width strand    source type score phase
1        1 12442003 12442535   533      - Cufflinks exon    NA    NA
2        1 12442642 12442922   281      - Cufflinks exon    NA    NA
3        1 12443021 12443186   166      - Cufflinks exon    NA    NA
      gene_id     isoform_id exon_number gene_name                   oId
1 XLOC_001339 TCONS_00001459           1       NAP VIT_01s0026g02710.t01
2 XLOC_001339 TCONS_00001459           2       NAP VIT_01s0026g02710.t01
3 XLOC_001339 TCONS_00001459           3       NAP VIT_01s0026g02710.t01
            nearest_ref class_code TSS_group_id CDS_id contained_in
1 VIT_01s0026g02710.t01          =      TSS1387  P1304         <NA>
2 VIT_01s0026g02710.t01          =      TSS1387  P1304         <NA>
3 VIT_01s0026g02710.t01          =      TSS1387  P1304         <NA>
      I'm curious only because in the CummeRbund manual the example gives:
      Code:
      > head(features(myGene))
 
   seqnames    start      end width strand source type score
1     chr1 20959948 20960428   481      + coding exon    NA
2     chr1 20964335 20964622   288      + coding exon    NA
3     chr1 20966385 20966485   101      + coding exon    NA
4     chr1 20970983 20971165   183      + coding exon    NA
5     chr1 20972053 20972216   164      + coding exon    NA
6     chr1 20974998 20975125   128      + coding exon    NA
  phase class_code exon_number     gene_id gene_name nearest_ref
1    NA          =           1 XLOC_000172     PINK1  uc001bdm.2
2    NA          =           2 XLOC_000172     PINK1  uc001bdm.2
3    NA          =           3 XLOC_000172     PINK1  uc001bdm.2
4    NA          =           4 XLOC_000172     PINK1  uc001bdm.2
5    NA          =           5 XLOC_000172     PINK1  uc001bdm.2
6    NA          =           6 XLOC_000172     PINK1  uc001bdm.2
         oId CDS_id     isoform_id TSS_group_id
1 uc001bdm.2   P364 TCONS_00000480       TSS264
2 uc001bdm.2   P364 TCONS_00000480       TSS264
3 uc001bdm.2   P364 TCONS_00000480       TSS264
4 uc001bdm.2   P364 TCONS_00000480       TSS264
5 uc001bdm.2   P364 TCONS_00000480       TSS264
6 uc001bdm.2   P364 TCONS_00000480       TSS264

      Comment

      Previous template Next

      Latest Articles

      Collapse
      • SEQadmin2
        Cancer Drug Resistance: The Lingering Barrier to Rising Survival
        by SEQadmin2



        Cancer survival rates have significantly increased in the last few decades in the United States, reaching a combined 70% 5-year survival rate by 2021. Behind this number, there are years of research to find new therapies, drug targets, and early detection methods. But there is one core challenge that keeps slowing down these advances, and it’s about drug resistance.

        There is no single reason why many patients don’t respond to treatment as expected. Cancer is...
        Today, 05:17 AM
      • GATTACAT
        Reply to Nine Things a Sample Prep Scientist Thinks About Before Sequencing
        by GATTACAT
        Love this - good data definitely starts from good input, and poor input can only give relatively poor data. I particularly like the mention of Nanodrop/absorbance based methods for quantification. It's such a toss up if you'll get an accurate reading or what amounts to a randomly generated number, and a lot of library/sequencing related issues can be traced back to poor quant.
        07-01-2026, 11:43 AM
      • SEQadmin2
        Nine Things a Sample Prep Scientist Thinks About Before Sequencing
        by SEQadmin2


        I’m not a sequencing expert. I’m a purification scientist who uses NGS to evaluate workflows my group develops. With this perspective, we think about the sample first and the NGS workflow second. The sequencer is an exceptionally honest reporter, but it can only report on what you give it, so whether you get clean, interpretable data from an NGS workflow is largely determined before you begin.

        Here are nine questions we think about, in roughly the order they matter, before...
        06-18-2026, 07:11 AM
      View All

      ad_right_rmr

      Collapse

      News

      Collapse
      Topics Statistics Last Post
      Genome-Wide CRISPR Screen Uncovers Unlikely Psoriasis Target by SEQadmin2
      Started by SEQadmin2, Today, 10:08 AM
      0 responses
      6 views
      0 reactions
      		 Last Post SEQadmin2
      by SEQadmin2
      Today, 10:08 AM  
      Engineered Protein Motor Takes Its First Steps Along DNA Track by SEQadmin2
      Started by SEQadmin2, Yesterday, 11:05 AM
      0 responses
      7 views
      0 reactions
      		 Last Post SEQadmin2
      by SEQadmin2
      Yesterday, 11:05 AM  
      High-Resolution Sequencing Exposes Hidden Toxoplasma Diversity by SEQadmin2
      Started by SEQadmin2, 07-02-2026, 11:08 AM
      0 responses
      30 views
      0 reactions
      		 Last Post SEQadmin2
      by SEQadmin2
      07-02-2026, 11:08 AM  
      New AI Model Captures Long-Range Genomic Signals to Improve RNA Splice Site Prediction by SEQadmin2
      Started by SEQadmin2, 06-30-2026, 05:37 AM
      0 responses
      28 views
      0 reactions
      		 Last Post SEQadmin2
      by SEQadmin2
      06-30-2026, 05:37 AM  
      View All
      Working...