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  • Pipeline for DESeq and annotation

    Hi, i am new to this and I would like to be able to feed my RNA data into the VST algorithm from DESeq, to normalize my data. But since there is so many different informations in here, I am not sure if I do it the right way, what I do is for each experiment/replicate:

    python tophat -p 8 -G genome.gtf -o output_dir genome.bt2 X1.fastq X2.fastq

    This generates a directory containing accepted_hits.bam

    I then sort this using

    Samtools sort –n input.bam out.sam

    I then run cufflinks and use the transcripts.gtf file

    cufflinks -p 8 -o newoutputDir outputdir/accepted_hits.bam

    To generate the list of counts I then do:

    htseq-count --stranded=no out.sam transcripts.gtf > output-htseq.txt

    which then gives me a list like this:

    CUFF.1 745
    CUFF.10 14
    CUFF.100 0
    CUFF.1000 1
    CUFF.10000 0
    CUFF.10001 1
    CUFF.10002 57


    Would this be a correct way of doing it? The output I get is just assigned to arbitrary values in the GTF file, and I have not been able to find that much about assigning the count values to gene identifiers, does anyone have any experience with that?
    Bjørn Øst

  • #2
    What is your input.bam? is that accepted_hits.bam?

    Comment


    • #3
      Are you looking for new genes, or do you you want to look for differential expression of known and annotated genes?

      If the former: Well, a new gene will not have a name; after all, it is new.

      If the latter: What did you run 'cufflinks' for?

      Comment

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