Computer for the analysis of high-throughput genomic data
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@steve-lianoglou-2771
Last seen 13 months ago
United States
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
Sequencing Microarray GO Network Cancer Sequencing Microarray GO Network Cancer • 758 views
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