Unconfigured Ad

Collapse
X
 
  • Time
  • Show
Clear All
new posts
  • gen2prot
    Member
    • Apr 2010
    • 68

    #1

    Repeatmasker run with crossmatch

    Hello All,

    I am running repeatmasker on a 2.1G genome that is assembled into 10 psuedomolecules. I am using the following parameter

    Code:
    -engine crossmatch -pa 32 -nolow -norna -cutoff 250 -gff
    I am running the job on the lsf cluster, but even after allocating sufficient memory and 32 processors per chromosome, its been running for 72 hours. I am using a database containing 3305 repeat sequences. Is there a method to increase the speed of the run?

    Please let me know.
    Thank you
  • Brian Bushnell
    Super Moderator
    • Jan 2014
    • 2709

    #2
    Depending on exactly what you are trying to do, you could certainly achieve the masking a lot faster (in a few minutes) using BBDuk instead via kmer-based masking. For example:

    Code:
    bbduk.sh in=genome.fa out=masked.fa k=31 ref=repeats.fa kmask=N
    That will mask everywhere that shares 31-mers with the reference. It also supports mismatches and sliding-window entropy masking. bbmask.sh is slightly more complete and can mask short repeats or mask a genome from an aligned sam file, and is also very fast.

    Comment

    • gen2prot
      Member
      • Apr 2010
      • 68

      #3
      Hi Brian,

      I would like to use the masked genome for repeat annotation. Does use of a kmer based masking tool lead to over masking? I would rather use a signature based masking tool like LTR_Struc, LTR_harvest in combination with Repeatmasker. What do you think?

      Thanks

      Comment

      • Brian Bushnell
        Super Moderator
        • Jan 2014
        • 2709

        #4
        That's an excellent question. I really don't know if it would be more or less sensitive, or better or worse, as I have l no direct experience with annotation. It might mask little regions in the middles of genes, for example (though you can circumvent that by using a very large K). Possibly a better solution would be to use a long read aligner and mask the regions the repeats align to. The big problem here is that I still don't understand the rationale for masking prior to annotation, but it seems to be due to some weakness in annotation algorithms - in other words, it's algorithm-specific rather than procedure-specific. If that's correct, that makes it impossible to determine the best method of masking (or whether masking is even beneficial) without a very deep understanding of the specific annotation algorithm.

        If you have some way of empirically determining the quality of annotation, though, it's certainly cheap to try alternative masking methods for comparison.

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