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Easiest way to compute RNA-Seq mapping stats (exons, introns, intergenic)?

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  • Easiest way to compute RNA-Seq mapping stats (exons, introns, intergenic)?

    I aligned RNA-Seq data to a genome using tophat2. Now I have the bam file and I am looking for a straight-forward way to produce mapping statistics - how many reads map onto exons, introns and intergenic regions.

    So my input consists of a bam file and the gtf file which I used with tophat2. What's the easiest way to get from this input to the output I need?

    If there is no off-the-shelf tool that would do this, please suggest a pipeline by specifying the steps that I need to make to get from the input to the desired output.

  • #2
    try qualimap qualimap.bioinfo.cipf.es

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    • #3
      The CollectRnaSeqMetrics program from the suite of Picard command-line tools will give you all of that data from the bam and gtf.

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      • #4
        A nice tool-box is RSeQc.
        You need your bam-file and an annotation in bed format to run read_distribution.py.

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        • #5
          Originally posted by cmbetts View Post
          The CollectRnaSeqMetrics program from the suite of Picard command-line tools will give you all of that data from the bam and gtf.
          I just googled it but it seems that CollectRnaSeqMetrics does not take as input GTF files. It requires RefFlat files. I am googling at the moment but cannot find documentation on how to convert gtf to RefFlat format.

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          • #6
            Originally posted by Michael.Ante View Post
            A nice tool-box is RSeQc.
            You need your bam-file and an annotation in bed format to run read_distribution.py.
            Thanks, Michael. I am not sure RSeQC would do the job as, to quote,
            RSeQC cannot assign those reads that hit to intergenic regions that beyond region starting from TSS upstream 10Kb to TES downstream 10Kb
            .

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