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  • SplicingCompass errors: argument is of length zero

    Hi,

    I am testing SplicingCompass for splicing differential expression analysis. Here is the steps:
    1. map the rnaseq reads to genome sequence using tophat
    2. prepare the gtf file produced by exseq_prepare_annotation.py of DEXSeq package.
    3. calculate the counts using coverageBed

    Then do the same R scripts as the SplicingCompasstutorial suggest, the
    checkExperimentInfo(expInf) command return TRUE, which suggest the "providing experimental information" step is correct.

    When I run the command and got the error message:
    Code:
    > countTable=constructCountTable(countTable,nCores=12,printDotPerGene=TRUE)
    Processing CoverageBed output files:
      |======================================================================| 100%
    Adding gene id column for convenience ...done
    Adding uniqe id column to table for convenience...done
    Adding exon numbers...done
    Adding RPKM values for every exon...done 
    Adding row means ...done
    Adding row meds...done
    Adding log ratios...done
    ====================  ...constructing junction dimensions (this will take some time)... ==============
    Reading reference annotation... 
     Preprocessing reference annotation (this may take a couple of minutes)...done
    processing G_1 
    processing G_2 
    processing S_1 
    processing S_2 
    using 12 cores ................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................... ............................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................Error in addColConnectsKnownConsecutiveExons(gffOfOneGene, junctionsGene) : 
      Junction connects more than two exons?
    
    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 |============                                                          |  17%Error in if (nrow(junctionMatrices[[i]]) > 0) junctionMatrices[[i]]$gene_id = geneIDs[i] : 
      argument is of length zero
    >      
    >
    What's wrong here?

    I guess it may be caused by the unprobable gtf annotation file.
    I paste several lines of them:
    Code:
    scaffold10135   dexseq_prepare_annotation.py    exonic_part     178842  179264  0.0000  +       .       mergedTranscriptIDs "TCONS_000
    25194"; exonic_part_number "001"; geneSymbol "XLOC_020700"
    scaffold10138   dexseq_prepare_annotation.py    exonic_part     144830  145048  0.0000  +       .       mergedTranscriptIDs "TCONS_000
    25196"; exonic_part_number "001"; geneSymbol "XLOC_020702"
    scaffold10138   dexseq_prepare_annotation.py    exonic_part     151927  151979  0.0000  +       .       mergedTranscriptIDs "TCONS_000
    25196"; exonic_part_number "002"; geneSymbol "XLOC_020702"
    scaffold10138   dexseq_prepare_annotation.py    exonic_part     169424  169664  0.0000  +       .       mergedTranscriptIDs "TCONS_000
    25196"; exonic_part_number "003"; geneSymbol "XLOC_020702"
    scaffold10138   dexseq_prepare_annotation.py    exonic_part     169424  169664  0.0000  +       .       mergedTranscriptIDs "TCONS_00025196"; exonic_part_number "003"; geneSymbol "XLOC_020702"
    scaffold10138   dexseq_prepare_annotation.py    exonic_part     188724  188960  0.0000  +       .       mergedTranscriptIDs "TCONS_00025196"; exonic_part_number "004"; geneSymbol "XLOC_020702"
    scaffold10138   dexseq_prepare_annotation.py    exonic_part     197955  198114  0.0000  +       .       mergedTranscriptIDs "TCONS_00025196"; exonic_part_number "005"; geneSymbol "XLOC_020702"
    scaffold10138   dexseq_prepare_annotation.py    exonic_part     209088  209291  0.0000  +       .       mergedTranscriptIDs "TCONS_00025196"; exonic_part_number "006"; geneSymbol "XLOC_020702"
    scaffold10138   dexseq_prepare_annotation.py    exonic_part     209982  210216  0.0000  +       .       mergedTranscriptIDs "TCONS_00025196"; exonic_part_number "007"; geneSymbol "XLOC_020702"
    scaffold10138   dexseq_prepare_annotation.py    exonic_part     215577  215763  0.0000  +       .       mergedTranscriptIDs "TCONS_00025196"; exonic_part_number "008"; geneSymbol "XLOC_020702"
    scaffold10138   dexseq_prepare_annotation.py    exonic_part     217793  217975  0.0000  +       .       mergedTranscriptIDs "TCONS_00025196"; exonic_part_number "009"; geneSymbol "XLOC_020702"
    scaffold1014    dexseq_prepare_annotation.py    exonic_part     84574   84743   0.0000  -       .       mergedTranscriptIDs "TCONS_00025199"; exonic_part_number "001"; geneSymbol "XLOC_020705"
    scaffold1014    dexseq_prepare_annotation.py    exonic_part     101674  101857  0.0000  -       .       mergedTranscriptIDs "TCONS_00025199"; exonic_part_number "002"; geneSymbol "XLOC_020705"
    scaffold1014    dexseq_prepare_annotation.py    exonic_part     121745  121897  0.0000  -       .       mergedTranscriptIDs "TCONS_00025199"; exonic_part_number "003"; geneSymbol "XLOC_020705"
    scaffold1014    dexseq_prepare_annotation.py    exonic_part     122021  122095  0.0000  -       .       mergedTranscriptIDs "TCONS_00025199"; exonic_part_number "004"; geneSymbol "XLOC_020705"
    scaffold1014    dexseq_prepare_annotation.py    exonic_part     137805  138013  0.0000  -       .       mergedTranscriptIDs "TCONS_00025199"; exonic_part_number "005"; geneSymbol "XLOC_020705"
    scaffold1014    dexseq_prepare_annotation.py    exonic_part     146499  146673  0.0000  -       .       mergedTranscriptIDs "TCONS_00025199"; exonic_part_number "006"; geneSymbol "XLOC_020705"
    scaffold1014    dexseq_prepare_annotation.py    exonic_part     154828  154938  0.0000  -       .       mergedTranscriptIDs "TCONS_00025199"; exonic_part_number "007"; geneSymbol "XLOC_020705"

  • #2
    I have tested with the gtf without any alternative splicing and got the same error message. Any suggestions will be appreciated.

    Comment


    • #3
      This error is caused by the old tophat mapping results. No error message appeared after using the results of latest tophat2. Thank you.

      Comment


      • #4
        same problem with RUM-mapped sam files

        i get the same error wuth RUM-mapped sam files.

        do you (or somebody else) know the differences between tophat1 and tophat2 produced sam files.

        perhaps i could fix the RUM-sam files...

        thank you,

        dietmar

        Comment


        • #5
          I donn't understand the meaning of this message "Junction connects more than two exons?" TopHat2 has been improved very much, you can have a try.

          I haven't used RUM.

          Comment


          • #6
            We had same error even if we use latest version of Tophat2.
            The version of the software we used are as follows.

            - Tophat: ver. 2.0.9
            - bowtie2: ver. 2.1.0
            - cuffdiff: ver. 2.1.1
            - R: 2.15.2
            - Bioconductor: 2.11
            - CummeRbund: 2.0.0

            I think this issue might not be fixed by updating TopHat2.

            Comment


            • #7
              Hi Pengchy,
              I'm trying to use a gtf from ensembl after running through dexseq's dexseq_prepare_annotation.py.
              I used it to creat the count files as well.

              This is what I did and the error I'm getting
              Code:
              > expInf=setReferenceAnnotation(expInf,"Homo_sapiens.GRCh37.69_dexseq.gtf")
              > referenceAnnotationFormat=list(IDFieldName="gene_id",idValSep=" ")
              > expInf=setReferenceAnnotationFormat(expInf,referenceAnnotationFormat)
              > checkExperimentInfo(expInf)
              [1] TRUE
              > countTable=new("CountTable")
              > countTable=setExperimentInfo(countTable,expInf)
              > countTable=constructCountTable(countTable,nCores=1,printDotPerGene=TRUE)
              using 1 core - please consider the multicore package to speed things up 
              Processing CoverageBed output files:
                |======================================================================| 100%
              Error in .getCountTable(x@expInf, asDataFrame = TRUE) : 
                Your processed reference annotation should only contain one type of feature
              I was wondering what referenceAnnotationFormat you were using? Or any other differences in the way you prepared the count table?

              Here's an example of the dexseq gtf:
              1 Homo_sapiens.GRCh37.69.gtf exonic_part 17233 17364 . - . transcripts "ENST00000538476+ENST00000430492+ENST00000541675+ENST00000438504+ENST00000537342+ENST00000423562+ENST00000488147"; exonic_part_number "019"; gene_id "ENSG00000227232"
              1 Homo_sapiens.GRCh37.69.gtf exonic_part 17365 17368 . - . transcripts "ENST00000430492+ENST00000488147+ENST00000423562+ENST00000537342"; exonic_part_number "020"; gene_id "ENSG00000227232"
              1 Homo_sapiens.GRCh37.69.gtf exonic_part 17498 17504 . - . transcripts "ENST00000541675"; exonic_part_number "021"; gene_id "ENSG00000227232"
              1 Homo_sapiens.GRCh37.69.gtf exonic_part 17602 17605 . - . transcripts "ENST00000538476+ENST00000438504"; exonic_part_number "022"; gene_id "ENSG00000227232"
              would it be better to use the gtf directly downloaded from ensembl?
              Here's an example of the ensembl gtf:
              5 protein_coding CDS 14398989 14399179 . + 2 gene_id "ENSG00000038382"; transcript_id "ENST00000344204"; exon_number "30"; gene_name "TRIO"; gene_biotype "protein_coding"; transcript_name "TRIO-001"; protein_id "ENSP00000339299";
              5 protein_coding exon 14401072 14401173 . + . gene_id "ENSG00000038382"; transcript_id "ENST00000344204"; exon_number "31"; gene_name "TRIO"; gene_biotype "protein_coding"; transcript_name "TRIO-001"; exon_id "ENSE00002752672";
              5 protein_coding CDS 14401072 14401173 . + 0 gene_id "ENSG00000038382"; transcript_id "ENST00000344204"; exon_number "31"; gene_name "TRIO"; gene_biotype "protein_coding"; transcript_name "TRIO-001"; protein_id "ENSP00000339299";
              5 protein_coding exon 14405957 14406099 . + . gene_id "ENSG00000038382"; transcript_id "ENST00000344204"; exon_number "32"; gene_name "TRIO"; gene_biotype "protein_coding"; transcript_name "TRIO-001"; exon_id "ENSE00002954951";
              Last edited by Maayanster; 10-01-2013, 12:29 PM.

              Comment

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