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
                  Beyond CRISPR/Cas9: Understand, Choose, and Use the Right Genome Editing Tool
                  by SEQadmin2



                  CRISPR/Cas9 sparked the gene editing revolution for both research and therapeutics.1 But this system still showed severe issues that limited its applications. The most prominent were the heavy reliance on PAM sequences, delivery limitations, double-stranded breaks that prompt unintended edits and cell death, and editing inefficiency (both in targeting and in knock-in reliability).

                  Despite this, “CRISPR helped turn genome editing from a specialized technique into
                  ...
                  07-31-2026, 11:01 AM
                • SEQadmin2
                  Proteomic Platforms: How to Choose the Right Analytical Strategy to Improve Detection and Clinical Applications
                  by SEQadmin2


                  Proteomics platforms are evolving rapidly, with advances in mass spectrometry and affinity-based approaches expanding what researchers can detect and at what scale. As the field moves toward deeper proteome coverage and clinical applications, scientists face an increasingly complex landscape of tools. This article will explore how researchers are navigating these choices to find the right platform for their work.

                  The systematic characterization of the human proteome has
                  ...
                  07-20-2026, 11:48 AM
                • SEQadmin2
                  Advanced Sequencing Platforms Tackle Neuroscience’s Toughest Genomics Problems
                  by SEQadmin2



                  Genomics studies in neuroscience face a special challenge due to the brain’s complexity and scarcity of samples. Mapping changes in cell type and state using conventional next-generation sequencing methods remains challenging. Advances in technologies like single-cell sequencing, spatial transcriptomics, and long-read sequencing have opened the door to deeper studies of the brain and diseases like Alzheimer’s, amyotrophic lateral sclerosis (ALS), and schizophrenia.
                  ...
                  07-09-2026, 11:10 AM

                ad_right_rmr

                Collapse

                News

                Collapse

                Topics Statistics Last Post
                Started by SEQadmin2, Today, 07:41 AM
                0 responses
                9 views
                0 reactions
                Last Post SEQadmin2  
                Started by SEQadmin2, 08-03-2026, 10:13 AM
                0 responses
                22 views
                0 reactions
                Last Post SEQadmin2  
                Started by SEQadmin2, 07-31-2026, 02:55 AM
                0 responses
                36 views
                0 reactions
                Last Post SEQadmin2  
                Started by SEQadmin2, 07-24-2026, 12:17 PM
                0 responses
                25 views
                0 reactions
                Last Post SEQadmin2  
                Working...