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  • horvathdp
    Member
    • Dec 2011
    • 66

    #1

    Low mapping of reads to trinity assembly

    Hi all,

    I am using iPlant resources, and I just finished doing an assembly of my RNAseq data using trinity (great results- ~200K contigs with N50 of ~1500, and mean of ~900- CEGMA giving 241 of the 248 conserved sequences as complete). With this in hand I used tophat2 to map my fragments as the first step to ID deferentially expressed transcripts. However, I am only getting about 38% of my fragments mapping to the Trinity contigs for any given sample. Is this expected? Is there a better way to do this? Any advice would be appreciated.

    Dave
  • flyingoyster
    Member
    • Aug 2011
    • 10

    #2
    I had similar problem, but even lower mapping rate (about 2%). What could be the problem? If you figure it out, please let know. Thanks!

    Comment

    • horvathdp
      Member
      • Dec 2011
      • 66

      #3
      More thoughts

      I think one of my problems is that at least 25% of the reads are too short to allow mapping of the paired ends. I am running TopHat2-SE to see if that significantly improves the percentage of mapped reads. I also assume that I lost any reads that didn't form contigs of at least 200 bases. I am not sure how to figure out what percentage that is. Any ideas from the experts out there?

      Finally, one more question for the experts: I plan on using the tuxedo suite to analyze my data- Mapping my trimmed sequences to the trintity contigs with tophat, usng Cuffmerge and Cuffdiff to ID differentially expressed genes. Is this a reasonable approach? Are there better approaches for mapping back to a denovo assembled transcriptome? Are there any problems I will likely encounter? Any advice will be appreciated.

      Comment

      • ddb
        Member
        • Feb 2012
        • 13

        #4
        What is the length of your reads and expected insert size / fragment length? The tuxedo suite is used when you have a genome sequence as reference. I do not think it is the right tool for denovo assembled contigs. For analyzing contigs I would look at Bowtie/Bowtie2 for mapping - RSEM/eXpress for abundance estimation and then one of the bioconductor tools for differential expression testing. I am sure others can suggest different tools. You could try following the Trinity protocol for downstream analysis.

        Comment

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