Unconfigured Ad

Collapse
X
 
  • Time
  • Show
Clear All
new posts
  • rjoyons
    Junior Member
    • Jul 2013
    • 4

    #1

    Using MetaVelvet, what hardware requirements?

    Hi everyone,

    I just received my very first set of shotgun-metagenomic sequencing results. They are illumina pair ended reads produced using the 2x250bp method. I have 26.5 million reads.

    My question is about the memory requirements of metavelvet.. In the manual it says the program requires "At least 12Gb of RAM (more is no luxury)" But they go onto use a computer with 48Gb of RAM to produce their example data in table 1 and the "required memory" for each assembly in tabel 1 is up to 72Gb.

    I'm finding this quite confusing! What happens when the memory requirement exceeds the amount of RAM on the workstation? Will the program crash or start making temporary files on the hard drive? Can you really use a computer with only 12Gb of RAM?

    Any advice would be greatly appreciated!! Please help!
  • student-t
    Member
    • Mar 2015
    • 16

    #2
    The approximate memory requirement is: number of nodes * 416 bytes because 416 bytes is the memory required for a node data-structure in C.

    Comment

    • bastianwur
      Member
      • Feb 2014
      • 98

      #3
      Originally posted by rjoyons View Post
      HWhat happens when the memory requirement exceeds the amount of RAM on the workstation? Will the program crash or start making temporary files on the hard drive?
      Default behaviour: First it'll use the swap, and if the swap gets nearly full, then the kernel will kill the program.

      Do you really have only 12 GB available?

      Apparently the Megahit assembler is really memory efficient, you might want to try that one.

      Comment

      • student-t
        Member
        • Mar 2015
        • 16

        #4
        This is also known as virtual memory, where the hard-disk space is being used for paging.

        Comment

        • Brian Bushnell
          Super Moderator
          • Jan 2014
          • 2709

          #5
          I'm hoping this project has been assembled by now. That said, Megahit is indeed quite efficient and we are now using it for metagenomes, with better results than Soap using a small fraction of the time and memory.

          If you run out of memory with assemblies, particularly metagenomes, it can be helpful to quality-trim, error-correct, and normalize the data first. This can greatly decrease the resource requirements (both time and memory) by reducing the volume of input reads and unique input kmers.

          Comment

          • student-t
            Member
            • Mar 2015
            • 16

            #6
            Brian, do know any paper that reviews it? I'm interested in knowing more.

            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, 08-03-2026, 10:13 AM
            0 responses
            17 views
            0 reactions
            Last Post SEQadmin2  
            Started by SEQadmin2, 07-31-2026, 02:55 AM
            0 responses
            33 views
            0 reactions
            Last Post SEQadmin2  
            Started by SEQadmin2, 07-24-2026, 12:17 PM
            0 responses
            23 views
            0 reactions
            Last Post SEQadmin2  
            Started by SEQadmin2, 07-23-2026, 11:41 AM
            0 responses
            21 views
            0 reactions
            Last Post SEQadmin2  
            Working...