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  • RNA-seq analysis

    I am doing RNA seq analysis for different gene expression analysis. I find that people use two approaches:

    1. Tophat - HtSeq - edgeR or DESeq R package
    2. Tophat - Cufflinks -Cuff Diff

    which approach that your guys use most? any advice?

  • #2
    I am in an early phase of my RNA-seq project and by now I'm using DESeq and edgeR for estimating modulated genes (DEG) and cufflinks /cuffcompare/cuffdiff for exploring differentially expressed transcripts, differential splicing and differential promoter use.

    if I also use cufflinks for estimating DEGs, I usually get some 50% DEGs in common with DESeq. DESeq and edgeR, on the other hand, share 80% of estimated DEGs.
    I am still experiencing things but I guess that the % of common DEG between DESEq and cufflinks is very much influenced by how you run cufflinks (reference GTF or not and other parameters as -R when running cuffcompare).
    I didn't try the latest cufflinks version yet, however. I used version 0.9.3

    It would be nice getting inputs on what others are doing !
    hope it helps,

    pbseq

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    • #3
      Just wanted to let you know that Cufflinks 1.0 has a completely revamped approach to DE that models over-dispersion of counts at the transcript level and we'll be curious to know how it performs on your tests.

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      • #4
        lpatcher,
        for sure I'll try soon latest version of cufflinks !

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        • #5
          Hello,

          I want to analyze my RNASeq data using DESeq. Would anyone tell me how and where to find codes for DESeq? Thx

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          • #6
            What do you mean by "codes"?

            We have written a nice manual (a "vignette") for DESeq, which you find here. We are currently overhauling it, and you'll find the improved vignette soon here.

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            • #7
              Thank you Simon.

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              • #8
                Hi Simon, how can I get TagSeqExample.tab file for practice?

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                • #9
                  I got it

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