Unconfigured Ad

Collapse
X
 
  • Time
  • Show
Clear All
new posts
  • shocker8786
    Member
    • Jan 2013
    • 28

    #1

    remove overlapping PE reads RRBS

    I'm working with PE RRBS data. The library fragment size is 40-220bp, and the reads are 50bp PE reads. Because of this, there are a significant amount of regions in which the PE reads overlap. I'm using BSseeker2 to align the PE data, but during the methylation calling there is a bias in the overlapping regions, as each read in an overlapping pair is used to call the methylation state. I need to avoid scoring overlapping methylation calls twice. However, this has proved to be harder than expected. I've tried two approaches:

    1. Remove the overlapping portion of one of the PE reads from the aligned bam file before methylation calling using BSeQC. I've tried this, and the output suggests that I have no overlapping PE reads:

    Total reads: 19725948
    Not unique paired mapping reads: 0(0.00%)
    Unique paired mapping reads: 19725948(100.00%)
    Skip not paired unique mapping reads: 0(0.00%)
    In unique paired mapping reads:
    All unique paired mapping basepairs: 932699172
    Filter end-repaired nucleotides in MspI site : 19714618(2.11% of u
    nique mapping basepairs)
    Filter overlapped basepairs: 0(0.00% of unique paired mapping base
    pairs)

    The results are the same for all of my samples. However I know that there are regions where PE reads do overlap. I'm not sure why BSeQC does not recognize this in my bam files produced by BSseeker2. So I decided to try another approach:

    2. Merge overlapping PE reads before alignment using SeqPrep. This results in about 10M of the ~19M reads being merged. However when I try to align these as SE reads, BSseeker2 seems to run properly, then stops partway through without any warnings or errors. I've looked through the output reports, but can't figure out where the problem is.

    Does anyone have any experience dealing with PE RRBS datasets? Bismark has an option to remove these overlapping portions, so I can switch to Bismark if I need to. But my % uniquely aligned drops about 10% or more using Bismark instead of BSseeker2 because Bismark does not allow the use of bowtie2 in the local alignment mode. Thanks.
  • dpryan
    Devon Ryan
    • Jul 2011
    • 3478

    #2
    Just use a different aligner. If you need local alignment then I recently updated bison to handle that. Bison will never double count overlapping portions of reads (unlike bismark, there's not even an option to enable that since it should never be done).

    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
      ...
      Today, 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, 02:55 AM
    0 responses
    7 views
    0 reactions
    Last Post SEQadmin2  
    Started by SEQadmin2, 07-24-2026, 12:17 PM
    0 responses
    12 views
    0 reactions
    Last Post SEQadmin2  
    Started by SEQadmin2, 07-23-2026, 11:41 AM
    0 responses
    12 views
    0 reactions
    Last Post SEQadmin2  
    Started by SEQadmin2, 07-20-2026, 11:10 AM
    0 responses
    24 views
    0 reactions
    Last Post SEQadmin2  
    Working...