Unconfigured Ad

Collapse
X
 
  • Time
  • Show
Clear All
new posts
  • medalofhonour
    Member
    • Jul 2011
    • 18

    #1

    Agilent SureSelect XT Capture vs. SureSelect XT2 Capture ? What's the difference ?

    I am trying to understand the difference between Agilent's Sureselect XT vs. XT2 exon captures.

    From what I understand, with XT2, you pool all of the samples together and then use the capture. (V4 Exome + UTR) while with XT, you use the capture individually on each sample.

    Is this understanding correct ?

    Sorry if this question is too naive, I am mainly a bioinformatics person trying to understand the process.

    From a Bioinformatics point of view, do you know if Agilent has separate BED files of targeted regions for XT and XT2 ? This is because I recently analyzed a set of samples, some of which were prepped using XT and others using XT2.

    And for the ones with XT2, we did not find many reads mapping in the regions defined by Agilent's V4 + UTR BED file ? But there were a good amount of reads mapping in these regions for the XT samples.

    Has anyone come across something like this before ?
  • Heisman
    Senior Member
    • Dec 2010
    • 534

    #2
    At least a year ago when I did targeted capture I was able to access the bed files of targeted regions through earray; is that possible now? I'd give that a try.

    Comment

    • medalofhonour
      Member
      • Jul 2011
      • 18

      #3
      Yes I have the BED file, but it's just one bed file for V4 Exome + UTR capture. I am wondering if there are separate BED files for XT and XT2 protocols ?

      This is because the BED file I am using gives me very low number of reads mapping in the target regions for the XT2 data.

      Comment

      • Cofactor Genomics
        Registered Vendor
        • Jan 2010
        • 52

        #4
        Have you run any qc on the data (FASTQC etc)? I would be suspect of the data and not the BED file if you are seeing few reads map back to the regions. I do not believe there are different BED files for pre and post-pooling captures.

        Have you taken the data and aligned to the reference genome, not the BED file, to see the percentage of reads that hit the genome? This will tell you at least if it is the right sample or if there is some other contamination going on. Something could have gotten mixed up before it came to you.

        There are quite a few other simply QC procedures that can be performed as it sounds like to me that it is a data problem and not an incorrect reference.

        Jon Armstrong
        Cofactor Genomics

        Comment

        • sprabhu
          Junior Member
          • Aug 2013
          • 1

          #5
          Hello,
          Did anyone figure out whether this was a bed file associated issue or whether it was the pre-capture (XT2) library prep steps that affected capture efficiency?
          Any updates on XT2 performance would be appreciated.
          Thanks

          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

          ad_right_rmr

          Collapse

          News

          Collapse

          Topics Statistics Last Post
          Started by SEQadmin2, Yesterday, 10:35 AM
          0 responses
          7 views
          0 reactions
          Last Post SEQadmin2  
          Started by SEQadmin2, 08-06-2026, 07:41 AM
          0 responses
          25 views
          0 reactions
          Last Post SEQadmin2  
          Started by SEQadmin2, 08-03-2026, 10:13 AM
          0 responses
          44 views
          0 reactions
          Last Post SEQadmin2  
          Started by SEQadmin2, 07-31-2026, 02:55 AM
          0 responses
          48 views
          0 reactions
          Last Post SEQadmin2  
          Working...