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  • fetch transcripts assembled by cufflinks

    Hi!

    I am an user of cufflinks. It's quite a good tool to estimate gene differential expression. However, our purpose is not only to test differentially expressed genes, but also to get these genes' sequences,which are assembled by cufflinks. We have used option -g in cufflinks and -r in cuffcompare.I try to fetch all the assembled transcripts by reading the locus of each assembled transcripts' exon from combined.gtf file produced by cuffcompare,then using samtools mpileup to parse whether a locus has a different base
    in mapped reads comparing to reference base of this locus, and finally joining these exons together to get full length sequences of assembled transcripts with IDs like "TCON...". However, I find that in combined.gtf,some exons' locus doesn't have any reads mapped at all, and if I continue the method I described before, I just wonder if I should use reference base in this locus, because this locus is actually not detected by real reads.


    I have read the manual of cufflinks in webset. I think the point is that in RABT model, cufflinks uses faux-reads to help assembling transcripts. It is quite helpful to detect new isoforms, However, when you try to get the real sequences of these isoforms, things became confusing. Do you have any suggestions to separate the real sequenced transcripted assembled by real reads from those reference trancripts assembled by faux-reads? In another word, how can I get the sequnces of each assembled transcripts from cufflinks?
    Thanks for help!


    asling

  • #2
    Any suggestion?

    Comment


    • #3
      I am facing the same problem: how can extract the assembled transcripts from RNA-seq data, NOT from reference genome.! Does anyone have any suggestions? I really appreciate.!

      Comment


      • #4
        Originally posted by seqfan05 View Post
        I am facing the same problem: how can extract the assembled transcripts from RNA-seq data, NOT from reference genome.! Does anyone have any suggestions? I really appreciate.!
        Hi seqfan05

        Have you sorted out the problem as I am facing the same problem and there is not much help reading posts.

        regards

        Comment


        • #5
          I'm having the same problem. I have RNAseq data that i analysed using the Tuxedo protocol. If i use the custom GTF file generated by cufflinks/cuffmerge then i can see there are lots of new splice variants but i can't see their sequence or the gene they most resemble. In addition, when you have multiple time points or treatment each containing hundreds or possible even thousands of new splicevarients how are you supposed to investigate them or describe these changes in splicevarient abundance? Splicegrapher looks like a nice way to investigate splicevarients but as far as i can see it only allows investigation of a few genes at a time http://splicegrapher.sourceforge.net/.

          Comment


          • #6
            Originally posted by Richard Barker View Post
            I'm having the same problem. I have RNAseq data that i analysed using the Tuxedo protocol. If i use the custom GTF file generated by cufflinks/cuffmerge then i can see there are lots of new splice variants but i can't see their sequence or the gene they most resemble. In addition, when you have multiple time points or treatment each containing hundreds or possible even thousands of new splicevarients how are you supposed to investigate them or describe these changes in splicevarient abundance? Splicegrapher looks like a nice way to investigate splicevarients but as far as i can see it only allows investigation of a few genes at a time http://splicegrapher.sourceforge.net/.
            I am sorry, I still can not find a way to address it. Can anybody help?

            Comment


            • #7
              here is the link that addresses this problem
              Application of sequencing to RNA analysis (RNA-Seq, whole transcriptome, SAGE, expression analysis, novel organism mining, splice variants)

              Comment

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