[R] Completely Off Topic:Link to IOM report on use of "-omics" tests in clinical trials

[Mike Marchywka]

Thanks, I had totally missed this controversy but from quick read of summary the impact on open source analysis was unclear.Can you explain the punchline? I think many users of R have concluded the biggest problem in most analyses isfirst getting the data and then verfiying any results you derive, both issues that sound related to your post.
( The jumble below is illustrative of what hotmail has been doing with plain text, getting plain data withoutall the formatting junk is a recurring problem LOL).





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> Date: Mon, 26 Mar 2012 22:38:56 +0100
> From: iaingallagher@btopenworld.com
> To: gunter.berton@gene.com; r-help@r-project.org
> Subject: Re: [R] Completely Off Topic:Link to IOM report on use of "-omics" tests in clinical trials
>
> I followed this case while it was ongoing.
>
>
> It was a very interesting example of basic mistakes but also (for me) of journal politicking.
>
>
> Keith Baggerly and Kevin Coombes wrote a great paper - "DERIVING CHEMOSENSITIVITY FROM CELL LINES: FORENSIC BIOINFORMATICS AND REPRODUCIBLE RESEARCH IN HIGH-THROUGHPUT BIOLOGY" in The Annals of Applied Statistics (2009, Vol. 3, No. 4, 1309–1334) which explains some of the background and investigative work they had to do to bring those mistakes to light.
>
>
> Best
>
> iain
>
>
>
> ----- Original Message -----
> From: Bert Gunter <gunter.berton@gene.com>
> To: r-help@r-project.org
> Cc:
> Sent: Monday, 26 March 2012, 19:12
> Subject: [R] Completely Off Topic:Link to IOM report on use of "-omics" tests in clinical trials
>
> Warning: This has little directly to do with R, although R and related
> tools (e.g. sweave and other reproducible research tools) have a
> natural role to play.
>
> The IOM report:
>
> http://www.iom.edu/Reports/2012/Evolution-of-Translational-Omics.aspx
>
> that arose out of the Duke Univ. genomics testing scandal has been
> released. My thanks to Keith Baggerly for forwarding this. I believe
> that many R users in the medical research community will find this
> interesting, and I hope I do not venture too far out of line by
> passing on the link to readers of this list. It **will** have an
> important impact on so-called Personalized Health Care (which I guess
> affects all of us), and open source analytical (statistical)
> methodology is a central issue.
>
> For those interested, try the summary first.
>
> Best to all,
> Bert
>
>
> --
>
> Bert Gunter
> Genentech Nonclinical Biostatistics
>
> Internal Contact Info:
> Phone: 467-7374
> Website:
> http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm
>
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