Unconfigured Ad

Collapse
X
 
  • Filter
  • Time
  • Show
Clear All
new posts
  • nareshmvr
    Member
    • Apr 2011
    • 16

    Preprocessing for good quality reports of FastQC for RNA-Seq

    Dear all,

    I am newbie to RNA-Seq data analysis(Illumina) , i have done quality check using FASTQC for the RNA-Seq data and now as per the manual for evaluating the FASTQC reports, i got good quality for all the sequences except "sequence duplicates" and "per base sequence content" where in the manual of evaluating the reports they mentioned they can be ignored for RNA-Seq data.

    In some forums i found irrespective of FASTQc reports , its a good idea to preprocess the data. so am confused how to preprocess the data for good quality reports of FASTQC , please suggest me in this about the tools and parameters for preprocessing good quality data , here am sending of my sample in the attachment. please suggest me if am wrong in this.
    Last edited by nareshmvr; 12-30-2014, 01:08 AM. Reason: image not sent
  • nareshmvr
    Member
    • Apr 2011
    • 16

    #2
    is my question wrong , please let me know if am wrong

    Comment

    • GenoMax
      Senior Member
      • Feb 2008
      • 7142

      #3
      "pre-processing" here is referring to use of a trimming program to scan your samples for adapter contamination? That is always a good idea irrespective of what the initial QC report says. You are not going to lose any information/make things worse by running BBDuk or Trimmomatic on your samples.

      Comment

      • nareshmvr
        Member
        • Apr 2011
        • 16

        #4
        thank you max ,

        i have bit experience in using prinseq , am using params -ns_max 0 and derep 14 to remove exact duplicates and ns , please suggest me in this

        Comment

        • GenoMax
          Senior Member
          • Feb 2008
          • 7142

          #5
          Take a look at this thread before you decide what to do with the duplicates: http://seqanswers.com/forums/showthread.php?t=33597

          Comment

          • nareshmvr
            Member
            • Apr 2011
            • 16

            #6
            sorry i think i made a wrong approach about my confusion in the pre-processing step, how to assess the parameters in pre-processing step for the FASTQC report of a RNA-Seq data .

            Comment

            • GenoMax
              Senior Member
              • Feb 2008
              • 7142

              #7
              Originally posted by nareshmvr View Post
              sorry i think i made a wrong approach about my confusion in the pre-processing step, how to assess the parameters in pre-processing step for the FASTQC report of a RNA-Seq data .
              Based on your original post it sounds like your data may already be of good quality and may not need additional processing.

              Comment

              Latest Articles

              Collapse

              • 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
              • 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

              ad_right_rmr

              Collapse

              News

              Collapse

              Topics Statistics Last Post
              Started by SEQadmin2, 07-24-2026, 12:17 PM
              0 responses
              30 views
              0 reactions
              Last Post SEQadmin2  
              Started by SEQadmin2, 07-23-2026, 11:41 AM
              0 responses
              23 views
              0 reactions
              Last Post SEQadmin2  
              Started by SEQadmin2, 07-20-2026, 11:10 AM
              0 responses
              213 views
              0 reactions
              Last Post SEQadmin2  
              Started by SEQadmin2, 07-13-2026, 10:26 AM
              0 responses
              79 views
              0 reactions
              Last Post SEQadmin2  
              Working...