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  • exon expression level

    Hi there.

    I would like to to get for a list of exons their expression level from my RNA-seq data.
    I thought about using cufflinks but the problem is that cufflinks generate FPKM at the isoform level. I usually feed cufflinks with a refseq gtf file downloaded from UCSC table browser (under genes and genes prediction), and cufflinks use that to build locus.
    I thought to switch back from locus to exons (using the ref ID NM/R_somenumber) but it's a wrong way to go by since:

    1) many exons participate in more than one transcript, and each has a different FPKM value
    2) FPKM number are probably calculated considering fragment length and each transcripts has its own, so I cannot just sum up the FPKM from all transcripts for a particular exon

    If I was in a world in which every gene had only one transcripts I guess my life would be easier and I would be blonde and handsome , but reality is crueler than that.

    All tables I can download on ucsc include variants so I got my hands on illumina truseq exome file containing all exons per gene in a definitively matter, meaning each exon appear once , even if some belongs to different variants. But it seems this file is no good for cufflinks and it was not able to build locus right.

    I thought of just using samtools for each exon:
    samtools view accpeted_hits.bam chr1:exonstrat-exonend | wc -l
    and just get and number and calculate my own FPKM using the exon's length (and total number of reads)

    Do you think using samtools is fine ?

  • #2
    Just use DEXseq and its python script for counting exonic bins. This is a solved problem. Yes, you'll get raw counts, but you can do whatever you want with those then.

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    • #3
      Do I need to install the whole package or can I just use this one script ?

      Comment


      • #4
        As I recall, the python scripts are just wrappers around htseq-count, so you can likely use them without the rest of the R package. Having said that, if you're interested in using the data to look at differential exon usage then DEXseq would be the tool to use anyway.

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        • #5
          As for now I only need the expression, will samtools be enough ?
          I would like to save the time of learning how to use this package as I'm not that familiar yet with R

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          • #6
            As long as you don't have paired-end reads, then yes, that'll work. You could also just
            Code:
            samtools view -c alignments.bam chr1:start-end
            since the -c option will do the counting for you.

            Comment


            • #7
              ok thank you for this help.

              I do have paired-end reads, but I guess I could write some script to handle that, using the reads ID.

              Nevertheless, I do preform differential exons analysis quite often, as I study alternative splicing, so it's about time I learn to use DEXseq anyhow.

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