Unconfigured Ad

Collapse
X
 
  • Time
  • Show
Clear All
new posts
  • IMPERATOR
    Junior Member
    • Jan 2014
    • 9

    #1

    Help a newbie: adapter filtering

    Hi all,

    I'm a virgin here, I was referred to this forum by a wonderful post-doc. Myself, I'm a first year PhD student so go easy on me...

    So I'm working with NGS data (duh) and I have a couple of questions.

    A little background. I have ~350 fastq paired end read files. Illumina hiseq I'm guessing.

    1. Is the adapter sequence the same for each file?

    2. How do I determine the adapter sequence? I've been using fastQC and under overrepresented sequences, I get this "GATCGGAAGAGCGTCGTGTAGGGAAAGAGGGTAGATCTCGGTGGTCGCCG"

    Now when I run my adapter filtering program, cutadapt for example, is the whole sequence my adapter? The post-doc truncated this sequence to "AGATCGGAAGAGC" is he right?

    I'm a little confused on the reasoning behind adapter filtering (I comprehend why you do it; to remove the adapter region which is not a part of the query sequence).

    Thanks for all the help.
  • GenoMax
    Senior Member
    • Feb 2008
    • 7142

    #2
    Here is a nice primer on TruSeq adapters: http://tucf-genomics.tufts.edu/docum...q_Adapters.pdf

    You could end up with adapter contamination if you have adapter dimers or have smaller than expected inserts. Since they are not part of real sequence you want to remove them (specially if you are going to do any de novo assembly).

    Ways of how to filter them:

    1. http://www.ark-genomics.org/events-o...-illumina-data

    2. http://onetipperday.blogspot.com/201...torprimer.html

    3. Trim Galore (http://www.bioinformatics.babraham.a...s/trim_galore/) is a wrapper for cutadapt (mentioned in both blog posts) that makes using cutadapt easy.

    4. Entire set of various illumina adapter sequences: http://support.illumina.com/download...es_letter.ilmn
    Last edited by GenoMax; 01-17-2014, 05:48 PM.

    Comment

    • IMPERATOR
      Junior Member
      • Jan 2014
      • 9

      #3
      Quick question, I'm working with a viral sequence ~10kb. Should I be less promiscuous with the filtering because of the small size?

      On the other hand, the coverage is quite good ~10,000x coverage. (DEEP SEQ HOMIE)

      Comment

      • GenoMax
        Senior Member
        • Feb 2008
        • 7142

        #4
        What is the aim of your experiment? Sometimes having too deep a coverage may actually be detrimental e.g. if you were trying to call SNV's.

        What % of your reads contain adapters?

        Comment

        • IMPERATOR
          Junior Member
          • Jan 2014
          • 9

          #5
          In a nutshell, we want to compare the sequences of virus in people that had successful treatment vs those who have failed.

          Eventually we would want to refine our techniques, both in vitro and in silico, in order to capture the viral population within each patient.

          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, Yesterday, 10:13 AM
          0 responses
          14 views
          0 reactions
          Last Post SEQadmin2  
          Started by SEQadmin2, 07-31-2026, 02:55 AM
          0 responses
          29 views
          0 reactions
          Last Post SEQadmin2  
          Started by SEQadmin2, 07-24-2026, 12:17 PM
          0 responses
          22 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...