Unconfigured Ad

Collapse
X
 
  • Time
  • Show
Clear All
new posts
  • ckidner
    Junior Member
    • Mar 2011
    • 5

    #1

    Transcriptome assembly using 12GB RAM?

    Is it possible to assemble a eukaryotic transcriptome from 50M Illumina paired end reads (101bp) using a machine with only 12 GB of RAM or am I going to have to find a bigger server? I've tried using Trinity, which can't manage it, but is there a more computationaly economical program I could use?
  • pbluescript
    Senior Member
    • Nov 2009
    • 224

    #2
    12GB is a tiny amount of RAM for an assembly. I would recommend getting more if you can.
    Otherwise, you could try Oases. I've had cases where assembly requires more RAM on Trinity than on Oases and vice versa.
    Besides that you could try removing poor quality reads, duplicate reads, or overlapping reads. Just be sure that the remaining reads are still paired in the fastq files.

    Comment

    • ckidner
      Junior Member
      • Mar 2011
      • 5

      #3
      Thanks, I'll look into more RAM. I was just hopeful as it had managed Newbler 2.5 assemblies of 454 data a year or so ago.

      Comment

      • Wallysb01
        Senior Member
        • Feb 2011
        • 286

        #4
        With that few of reads you *might* be able to manage it will ABySS/Trans-ABySS. I'd suggest doing some quality trimming (Q=20 is usually reasonable) and excluding unique kmers to decrease your memory footprint. But with a modern desktop computer you should really be able to get up to 32 GB of RAM for pretty cheap. If you do this much its worth the extra $100-200.

        Comment

        • pbluescript
          Senior Member
          • Nov 2009
          • 224

          #5
          With 454, you get longer reads, so assembly is generally a less memory intensive process. Do your Illumina reads overlap? If so, you could try a program to merge them. That would decrease your read number but maintain the information and could reduce the amount of RAM needed.

          Comment

          • ymc
            Senior Member
            • Mar 2010
            • 496

            #6
            Is 64GB enough for illumina human transcriptome assembly with about 100mil 100bp reads?

            Comment

            • pbluescript
              Senior Member
              • Nov 2009
              • 224

              #7
              Originally posted by ymc View Post
              Is 64GB enough for illumina human transcriptome assembly with about 100mil 100bp reads?
              It could be. Try it and see.

              Comment

              • Mark
                Member
                • Nov 2008
                • 54

                #8
                You could also try limiting over abundant reads and removing very low frquency (often erroneous) reads via the Titus Brown's khmer package. This can greatly reduce the size of your dataset without greatly affecting your assembly

                Comment

                Latest Articles

                Collapse

                • SEQadmin2
                  Multiomic Liquid Biopsy: What DNA/RNA Panels Reveal That DNA Alone Can’t
                  by SEQadmin2



                  Tumors contain complex mixtures of cell populations that evolve in response to treatment and host-specific factors. Tissue biopsies provide only static snapshots of a tumor’s state. But what if we could follow that evolution over time using a minimally invasive technique?

                  Liquid biopsies can detect tumor-derived material circulating in the bloodstream, providing a way to study treatment response, detect emerging resistance, and discover new biomarkers. Circulating
                  ...
                  10-14-2026, 09:55 AM
                • SEQadmin2
                  New Genomics Technologies Take Aim at Long-Standing Limits
                  by SEQadmin2


                  Researchers using sequencing and genomics tools often have to make trade-offs. They can choose between speed or scale, short reads or long-range information, or targeted panels or a view of the whole transcriptome. New technologies that have been released this year are built to address those tough choices.

                  We asked six companies the same four questions to learn about their latest products. The new technologies bring a lot to the table, including rethinking sequencing
                  ...
                  09-28-2026, 10:25 AM

                ad_right_rmr

                Collapse

                News

                Collapse

                Topics Statistics Last Post
                Started by SEQadmin2, 10-15-2026, 10:52 AM
                0 responses
                17 views
                0 reactions
                Last Post SEQadmin2  
                Started by SEQadmin2, 10-14-2026, 05:39 AM
                0 responses
                26 views
                0 reactions
                Last Post SEQadmin2  
                Started by SEQadmin2, 10-13-2026, 09:56 AM
                0 responses
                22 views
                0 reactions
                Last Post SEQadmin2  
                Started by SEQadmin2, 10-09-2026, 11:14 AM
                0 responses
                28 views
                0 reactions
                Last Post SEQadmin2  
                Working...