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Percentage Of Successful Next Generation Sequencing Projects ?

I've been regularly asked to analyse a set of BAM/VCF related to some genetic diseases.

The studied phenotypes are now more and more complicated (e.g: multigenic, not a non-synonymous mutation, etc... ) and I've got the feeling that the good results are more scarce (depressing).

Is there a resource that would highlight the number of NGS projects vs the number of articles published ?

Thank you,

Pierre

next-gen
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updated by Istvan Albert Istvan Albert • written by Pierre Lindenbaum Pierre Lindenbaum

Are you specifically asking about NGS projects aiming at detecting genomic variants related to some disease (basically GWAS-type)? I work on several (successful) projects that include NGS (genomics, transcriptomics, ...), so I think your question's title is misleading.

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written by Leonor Palmeira Leonor Palmeira

If you could get data on library prep kits ordered or lanes sequenced and then compare that to papers published somehow, I think it would paint quite a disappointing picture...

Getting data on a widespread scale might be harder, but maybe for a single institution it would be possible.

As a colleague has been known to say "Science is hard."

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written by Madelaine Gogol Madelaine Gogol

What do you even mean by successful? If a sequencing project gives a lab 10 candidate genes, that can be a huge success, whether it's published or not. Sure, it might take a decade to work out the details of which gene is causative, and another decade to develop treatments, but giving wet-lab folks a narrowly focused place to start can be invaluable.

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written by Chris Miller Chris Miller

1 answer

A really good blog to follow on the mater is Mass Genomics it is quite eye-opening to see just hard it is to actually correlate genomic data with diseases.

On top of that a high percentage of even the 'best' studies may later turn out to be called into question. This post: http://massgenomics.org/2012/02/agbt-2012-day-1-clinical-annotation-and-fierce-competition.html sums it up like so: Next-gen Sequencing: Lots of Data, Not Many Findings

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written by Istvan Albert Istvan Albert

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