Unconfigured Ad

Collapse
X
 
  • Filter
  • Time
  • Show
Clear All
new posts
  • cerebralrust
    Junior Member
    • Jan 2012
    • 8

    Extent of reduction during pre-processing

    I'm just curious as how much reduction others observe during pre-processing of ngs data.

    I've got 454 rna-seq data of about 300,000 reads.
    Based on the fastqc report and using fastx toolkit,
    - removing reads with bases below quality score of 20
    - removing reads containing Ns
    -removing ribosomal rna sequences (167 using bwa)
    -removing reads below 100bp length

    the dataset reduced to 185,735. I felt like this is too small. Is such a reduction common?
    I could retain the reads less than 100bp in length , align them separately and align the entire dataset again.

    I appreciate any advice and/or insight. Thank you.
  • westerman
    Rick Westerman
    • Jun 2008
    • 1104

    #2
    It does seem like you are being rather strict. While it depends on your project and the program you wish to use, most NGS programs are rather insensitive to poor quality and short reads. Thus I rarely eliminate these. Of course rRNA can mess up a project as can adapter sequences so it can be useful to remove (or trim) reads that match those sequences.

    Comment

    • cerebralrust
      Junior Member
      • Jan 2012
      • 8

      #3
      Thank you very much for your reply, Rick!

      I'm using both MIRA and Trinity for assembly. Trinity is supposedly less sensitive to low quality compared to MIRA.

      Anyhow, i will stick to removal of rRna and trimming adaptor sequences prior to assembly.

      Thanks a lot!

      Comment

      • Manal
        Junior Member
        • Apr 2013
        • 8

        #4
        Hi All
        I have one basic question, I am new in the NGS field / Illumina and little bit confused about the meaning of Phasing and Prephasing rate and how does it happen?
        Can anyone explain ?

        Thanks

        Comment

        • mastal
          Senior Member
          • Mar 2009
          • 666

          #5
          Extent of reduction during pre-processing

          See the explanation in the Rationale section of this paper:



          Basically phasing/prephasing refers to the problem that not all the molecules in a cluster on the flow cell will successfully incorporate a base during each cycle, or some may incorporate more than 1 base.

          Comment

          Latest Articles

          Collapse

          • 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
          • SEQadmin2
            Cancer Drug Resistance: The Lingering Barrier to Rising Survival
            by SEQadmin2



            Cancer survival rates have significantly increased in the last few decades in the United States, reaching a combined 70% 5-year survival rate by 2021. Behind this number, there are years of research to find new therapies, drug targets, and early detection methods. But there is one core challenge that keeps slowing down these advances, and it’s about drug resistance.

            There is no single reason why many patients don’t respond to treatment as expected. Cancer is...
            07-08-2026, 05:17 AM
          • GATTACAT
            Reply to Nine Things a Sample Prep Scientist Thinks About Before Sequencing
            by GATTACAT
            Love this - good data definitely starts from good input, and poor input can only give relatively poor data. I particularly like the mention of Nanodrop/absorbance based methods for quantification. It's such a toss up if you'll get an accurate reading or what amounts to a randomly generated number, and a lot of library/sequencing related issues can be traced back to poor quant.
            07-01-2026, 11:43 AM

          ad_right_rmr

          Collapse

          News

          Collapse

          Topics Statistics Last Post
          Started by SEQadmin2, 07-13-2026, 10:26 AM
          0 responses
          20 views
          0 reactions
          Last Post SEQadmin2  
          Started by SEQadmin2, 07-09-2026, 10:04 AM
          0 responses
          31 views
          0 reactions
          Last Post SEQadmin2  
          Started by SEQadmin2, 07-08-2026, 10:08 AM
          0 responses
          20 views
          0 reactions
          Last Post SEQadmin2  
          Started by SEQadmin2, 07-07-2026, 11:05 AM
          0 responses
          34 views
          0 reactions
          Last Post SEQadmin2  
          Working...