[BioC] Computer for the analysis of high-throughput genomic data

[Steve Lianoglou]

Hi Alberto,

Sorry to continue a bit of an OT thread, but I thought this would be
useful to share:

I just stumbled onto this blog post about a "reasonable" HPC system
for a small bioinformatics lab -- if you're on a budget, this looks
pretty good to me!

http://thegenomefactory.blogspot.com/2012/10/building-bioinformatics-server-on.html

In short:

* 3.2 Ghz 6 core CPU (12 threads)
* 64 GB RAM
* 12TB of storage (RAID 6 (software, not hardware))

~ $2,600 (US)

It's not a hardware RAID, and no ECC memory, but it makes a rather
serviceable machine -- and at that price ... heck, get a couple! ;-)

No idea what to expect for maintenance costs, though ...

HTH,
-steve

-- 
Steve Lianoglou
Graduate Student: Computational Systems Biology
 | Memorial Sloan-Kettering Cancer Center
 | Weill Medical College of Cornell University
Contact Info: http://cbio.mskcc.org/~lianos/contact

On Fri, Dec 28, 2012 at 11:12 AM, Capurro, Alberto  (Dr.)
<ac331 at leicester.ac.uk> wrote:
> Thank you very much Steve, I will go for a linux operating system then.
>
> Best,
>
> Alberto
>
>
>
> Alberto Capurro
> Marie Curie Research Fellow
> Department of Cell Physiology and Pharmacology
> College of Medicine, Biological Sciences and Psychology
> Maurice Shock Medical Sciences Building Room 319
> University of Leicester
> Leicester LE1 9HN
> United Kingdom
>
> Tel +44 (0)116 252 2673
> E-mail: ac331 at le.ac.uk
> https://sites.google.com/site/albertocapurro/
> ________________________________________
> From: Steve Lianoglou [mailinglist.honeypot at gmail.com]
> Sent: Friday, December 28, 2012 3:52 PM
> To: Capurro, Alberto (Dr.)
> Cc: bioconductor at r-project.org
> Subject: Re: [BioC] Computer for the analysis of high-throughput genomic data
>
> Hi,
>
> On Fri, Dec 28, 2012 at 4:36 AM, Capurro, Alberto  (Dr.)
> <ac331 at leicester.ac.uk> wrote:
>> Thank you very much. I will do microarray analysis at first but in the future we are also interested in sequencing. The computer is for the lab, I will be in charge of the processing, I have experience in computational neuroscience but not in genomics, so I am learning now. I think that the Uni  usually buys windows machines. Regarding the operating system, is there an important reason to use linux instead of windows 7 to run bioconductor and R?. I can use linux if it is better. I can get 10 T and backup in and external disk and in space provided by the Uni network.
>
> Without inciting a flamewar, I don't think it's too controversial to
> say that most scientific tools in this space are written for linux
> first, then tweaked to run on osx (us osx folks are, by default, stuck
> on an older version of gcc, so some tweaks are harder than others),
> and likely windows is the after thought.
>
> Look at, for example, some of the aligners out there.
>
> * Bowtie provides compiled binaries for linux and osx, no windows:
>   http://sourceforge.net/projects/bowtie-bio/files/bowtie2/2.0.4/
>
> * The STAR aligner runs on linux, and recently was tweaked to run on
> osx (not sure if it's entirely working).
>
> * bwa's SF page suggests it only runs on linux and BSD (osx).
>
> * "A unix system" is listed as a prerequisite for installing GSNAP.
>
> For the most part, however, this isn't true for the R/bioconductor
> packages you will likely be using. AFAIK, the majority of the bioc
> packages work just fine on unix, osx, and windows.
>
> Also, if you're planning on having several people log into the machine
> to do work, then I think a *nix is likely going to be your best bet.
>
> So, to be honest, even though I have a slight osx bent, if I were in
> your shoes and was put in a position to buy a workhorse machine, I'd
> go linux. I assume you, and the other members in the lab, will have
> their own desktops/laptops to do downstream analysis -- which can be
> the OS of your choosing.
>
> After doing some of the heavy lifting on a compute-server (I'm
> thinking of alignment/assembly), you can likely do most all of your
> work on a lower powered machine -- especially if we're talking about
> more "canned"/routinary analysis. I've done lots of downstream
> analysis on my 8gb ram, dual core macbook pro, for instance, although
> having access to some big iron to do some heavy computing at times is
> totally necessary.
>
> HTH,
> -steve
>
> --
> Steve Lianoglou
> Graduate Student: Computational Systems Biology
>  | Memorial Sloan-Kettering Cancer Center
>  | Weill Medical College of Cornell University
> Contact Info: http://cbio.mskcc.org/~lianos/contact



-- 
Steve Lianoglou
Graduate Student: Computational Systems Biology
 | Memorial Sloan-Kettering Cancer Center
 | Weill Medical College of Cornell University
Contact Info: http://cbio.mskcc.org/~lianos/contact