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  • kirstyn
    Junior Member
    • May 2012
    • 8

    #1

    Analysing .ace and .bam files for SNPs

    Hi

    I have imported .ace files from 454 sequencing into both Geneious and Seqman pro. I want to find SNPs in reads and currently the analysis only highlights insertions and deletions. This is because the reads import with gaps (dashed lines) for every single variation, which means that for my ~6kb sequence I have an 18kb contig. How can I remove these gaps so that the SNP analysis works properly?

    I would appreciate any help with this!

    Thanks
  • maubp
    Peter (Biopython etc)
    • Jul 2009
    • 1544

    #2
    It sounds like you are running into the issue where Newbler tends to use a deletion/insertion rather than a mismatch for a SNP. Is that a fair guess?

    Comment

    • kirstyn
      Junior Member
      • May 2012
      • 8

      #3
      Yes that's right. Is there no way to get around this?

      Comment

      • kirstyn
        Junior Member
        • May 2012
        • 8

        #4
        I've found a thread discussing this problem....

        Comment

        • colindaven
          Senior Member
          • Oct 2008
          • 417

          #5
          That issue drove me crazy for a bit. We ended up using alternative 454 mappers for alignment, eg CLC genomics workbench, bwa-sw, or others discussed on this forum.

          Comment

          • kirstyn
            Junior Member
            • May 2012
            • 8

            #6
            It has been driving me crazy too! What was your experience from using alternative mappers? Have you attempted to use MIRA, which was mentioned in the other post?

            Comment

            • sklages
              Senior Member
              • May 2008
              • 628

              #7
              Originally posted by kirstyn View Post
              It has been driving me crazy too! What was your experience from using alternative mappers? Have you attempted to use MIRA, which was mentioned in the other post?
              Should do the job. Leads you on the Staden/gap5 track.
              If you are familiar with Consed, you could also use it for your mapping of 454 data (it internally uses cross_match).

              Comment

              • colindaven
                Senior Member
                • Oct 2008
                • 417

                #8
                Otherwise novoalign should do the job pretty well, and the free version should be fast enough.
                Keep in mind they automatically trim to 160bp (or used to at least), which should be disabled for 454 reads.

                I have always had problems with bwa-sw and segmentation faults.

                Clcgenomics worked well but was very expensive.

                Comment

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