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  • tedwong
    replied
    We have started a formal thread for current and future users to discuss DNA sequins:

    http://seqanswers.com/forums/showthr...786#post197786

    or RNA sequins:

    http://seqanswers.com/forums/showthread.php?t=70843

    Enjoy!

    Leave a comment:


  • tedwong
    replied
    Hi nucacidhunter,

    DNA sequins can be used with any sequencing platform. An application where the combination of long-read sequencing (eg PacBio) and Sequins will be particularly powerful is in the detection of structural variation (which we all know is a major challenge). Our current generation of Sequins includes longer standards that emulate large deletions, inversions, tandem duplications, novel sequence insertions and mobile element insertions, all based on real instances of human variation.

    Cheers

    Ira Deveson (on behalf of the Sequins team)

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  • nucacidhunter
    replied
    It will be good if they can design longer DNA Sequins for PacBio or 10x Genomics Chromium platform.

    Leave a comment:


  • GenoMax
    started a topic Spike-in controls

    Spike-in controls

    Spike-in controls is one of the oft discussed topics on SeqAnswers.

    Researchers at the Garvan Institute of Medical Research have just published two papers in Narure Methods about synthetic DNA and RNA standards that can be used as spike-in controls.

    Deveson et al: http://www.nature.com/nmeth/journal/...meth.3957.html

    DNA Controls

    Sequencing reads derived from sequins align exclusively to an artificial in silico reference chromosome, rather than the human reference genome, which allows them them to be partitioned for parallel analysis.
    Hardwick et al: http://www.nature.com/nmeth/journal/...meth.3958.html

    RNA Controls

    Sequins have an entirely artificial sequence with no homology to natural reference genomes, but they align to gene loci encoded on an artificial in silico chromosome. The combination of multiple sequins across a range of concentrations emulates alternative splicing and differential gene expression, and it provides scaling factors for normalization between samples.
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