Unconfigured Ad

Collapse
X
 
  • Filter
  • Time
  • Show
Clear All
new posts
  • poorphd
    Junior Member
    • Jul 2011
    • 3

    how to define a forward or reverse read file

    i often meet the concept of "forward" or "reverse".
    but not exact definition provided

    does the "forward" means the reads who have the same direction with PCR primer 1 ?
    does the "reverse". means the reads who have the same direction with PCR primer 2 ?

    thank u very much
    shan gao
  • Soleil
    Junior Member
    • Nov 2011
    • 2

    #2
    In relation to your sequence:
    Forward: 5' to 3'
    Reverse: 3' to 5'

    Comment

    • poorphd
      Junior Member
      • Jul 2011
      • 3

      #3
      no, not that simple

      In classical biology, we define "Forward" is the direction from 5' to 3' and "Reverse". 3' to 5'. but in NGS sequencing, all the sequences direction is from 5' to 3' , so F means sense strand, and R means anti sense.but in classical biology, we define sense strand is mRNA direction. those concepts are a little confusing.

      and also in the Trinity algorithm, i think sense or antisense is just oppossite to each other. if you define one srtand is sense, the other one is antisense. trinity donot care which one is which one. i think you design this parameter --SS_lib_type, just to make the output sequences following
      the sense direction which defined by users.

      Comment

      • swbarnes2
        Senior Member
        • May 2008
        • 910

        #4
        I would agree with Soleil...the way people use forward and reverse in NGS context, the forward read is the one that is in the same direction as your reference, and the reverse is the one that is in the opposite direction. Of course, what might be forward for a genone might be reverse when talking about a transcript.

        If you were doing something other than an ordinary genomic prep, like you were doing PCR, with the adaptors incorporated into the PCR primers, and putting that product onto the flow cell, then there would be a solid correlation between read 1 and the direction of the read itsself, with respect to the reference. But with ordinary genomic-type preps, the DNA gets sheared, and adaptors are ligated, and they don't know which way the DNA was oriented with respect to the telomere, or whether your reference puts the telomere at the start or the end of your refeence. So reads go in all directions. So really, all that matters is that for each cluster, read 1 runs one way, and read 2 runs the other way; towards each other in paired end, away from each other in mate-pair.

        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...