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  • colin_c
    Junior Member
    • Jun 2014
    • 5

    Opinion on Hardware

    Hi All,

    I'm currently in the process of buying a workstation for RNA-seq expression analysis (mRNA, miRNA, lnRNA snoRNA).

    I was wondering what people thought of the following hardware:

    HP Z820 Workstation
    2 Xeon E5-2687Wv2 3.40Ghz 25MB 1866 8C
    256GB DDR-3-1866 (8 X 32GB) 2CPU LR RAM
    4 x 2TB 7200 SATA
    RAID 5

    Thanks!
    Colin
  • dpryan
    Devon Ryan
    • Jul 2011
    • 3478

    #2
    Looks good. The RAM is a bit overkill for what you're doing at the moment, but of course it's better to have it and not need it than to need it and not have it

    Comment

    • colin_c
      Junior Member
      • Jun 2014
      • 5

      #3
      Originally posted by dpryan View Post
      Looks good. The RAM is a bit overkill for what you're doing at the moment, but of course it's better to have it and not need it than to need it and not have it
      Thanks for the reply! Is there an arguments for decreasing the RAM to 128GB and increasing the number of cores to 24?

      Colin

      Comment

      • dpryan
        Devon Ryan
        • Jul 2011
        • 3478

        #4
        128 is still enough for things like STAR, which might benefit from the increased core availability (though I've never benchmarked that). If you're planning to use DEXSeq or anything like that, then the increased number of cores would be beneficial. I can't think of anything normally used in RNAseq that'll need more than 128GB memory, though if you're going to need to assemble the transcriptomes (i.e., you're not using one of the common model organisms) then perhaps that'll need it (it's not something I ever need to do, so I can't provide any advice there).

        Comment

        • colin_c
          Junior Member
          • Jun 2014
          • 5

          #5
          Originally posted by dpryan View Post
          128 is still enough for things like STAR, which might benefit from the increased core availability (though I've never benchmarked that). If you're planning to use DEXSeq or anything like that, then the increased number of cores would be beneficial. I can't think of anything normally used in RNAseq that'll need more than 128GB memory, though if you're going to need to assemble the transcriptomes (i.e., you're not using one of the common model organisms) then perhaps that'll need it (it's not something I ever need to do, so I can't provide any advice there).
          The majority of my work involves a non model organism so transcriptome assembly is a possibility.

          In terms of the number of cores, I guess the trade off is run time?

          Thanks!
          Colin

          Comment

          • dpryan
            Devon Ryan
            • Jul 2011
            • 3478

            #6
            Yeah, more cores will generally decrease run time (to a point, at least).

            Comment

            • colin_c
              Junior Member
              • Jun 2014
              • 5

              #7
              Originally posted by dpryan View Post
              Yeah, more cores will generally decrease run time (to a point, at least).
              Thanks for you help! Much appreciated!

              Comment

              • GenoMax
                Senior Member
                • Feb 2008
                • 7142

                #8
                SATA disks probably would become the bottleneck with a large number of cores. You should probably stick with your original configuration but you may want to include a good (intel) SSD for your OS.

                Comment

                • Brian Bushnell
                  Super Moderator
                  • Jan 2014
                  • 2709

                  #9
                  If you want to do assembly of eukaryotes, I do not recommend increasing core-count at the expense of memory. 256g will already be limiting in some scenarios, depending on the size of the organisms you're working with. Many assemblers do not scale well with large numbers of processors, anyway, though mappers should scale linearly.

                  Comment

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