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  • how to analyze multiple samples using tophat

    I have RNA-seq data from different experiments. How can I analyze multiple samples together using tophat? I tried command as below

    tophat -o output_dir --solexa1.3-quals --num-threads 12 hg19 rna_seq/raw_data/cancer_sequence.txt,rna_seq/raw_data/control_sequence.txt"

    It seems the result only has one .accepted_hits.bam file and one junctions.bed file. I thought there should have different outputs for each sample. Should I run tophat for each sample separately??

    Thanks!

  • #2
    One more question here. I plan to use Cufflinks that uses tophat outputs. It seems Cufflinks only accept one input SAM file. Should I first parse the accepted_hits.bam to get SAM files for each sample and then input them separately to Cufflinks for expression quantification?

    What is the good way to use the tophat-cufflinks pipeline?

    Much appreciated!!!

    Comment


    • #3
      I am learning how to use TopHat, and I do have exactly the same question. Do you happen to know the answer?

      Aurelien

      Comment


      • #4
        Me too. I ran into the same problem... Any idea?

        Comment


        • #5
          It's not really a straightforward problem, especially since the documentation for tophat/cufflinks is quite sparse - but what I do at the moment is
          • tophat each sample separately (pooling technical replicate lanes at this step)
          • cufflinks each sample separately
          • cuffcompare all the samples, using the -G option providing an ensembl gtf of gene annotations to create a new gtf containing ensembl genes and any novel transcripts discovered by tophat/cufflinks
          • cuffdiff samples against each other using the new gtf created in the previous step (pooling biological replicates at this step)


          Any suggestions?

          Comment


          • #6
            Hi all. definitely search around on this site. there are a lot useful answers if you look hard enough, but it does take some patience. I can suggest at least a few threads (below). Good luck!

            Jamie

            Discussion of next-gen sequencing related bioinformatics: resources, algorithms, open source efforts, etc


            Discussion of next-gen sequencing related bioinformatics: resources, algorithms, open source efforts, etc


            Application of sequencing to RNA analysis (RNA-Seq, whole transcriptome, SAGE, expression analysis, novel organism mining, splice variants)

            Comment

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