Seqanswers Leaderboard Ad

Collapse

Announcement

Collapse
No announcement yet.
X
 
  • Filter
  • Time
  • Show
Clear All
new posts

  • As GenoMax says, trimming to Q30 is not beneficial before merging reads. BBMerge has some internal quality-trimming options, so it can try to merge, then quality-trim if it is unsuccessful, then try to merge again, etc. That can slightly increase the merge rate. But typically I just use the whole untrimmed reads as input. The longer the input reads are, the less likely it is for BBMerge to make an accidental incorrect merge, and it does take quality scores into account, so I do not recommend quality-trimming prior to BBMerge. Adapter-trimming is fine though.

    Comment


    • Hello Brian,

      Originally posted by Brian Bushnell View Post
      Aapter-trimming is fine though.
      Do you recommend adapter trimming prior use of bbmerge? I thought if I provide the adapter sequence to bbmerge, it can find those paires which completly overlap more easy.

      fin swimmer

      Comment


      • Merge pairs before normalisation?

        Hello, I'm building a pipeline for metagenomics.

        I follow the bb tools user guide and do:
        - normalization with bbnorm
        - error correction with tedpole
        - merge (with extension) with bbmerge

        I want to increase the merging to get a better assembly.
        I suspect that many reads, which could be merge are thrown away during the normalisation.

        Wouldn't it be better to do merging (without extension) first than taking primarily the merged reads, normalize, error-correct and merge with extension?

        What is the best way of normalising paired end and merged pairs or singletons in bbnorm?
        For now I do two rounds of bbnorm and supply the other reads via the `extra` parameter, is there a better way to do?

        Comment


        • Hi,

          I have the shotgun data. Paired-end reads 100bp each end. I want to do MetaPhlAn2 next to know the general taxonomy profile.

          So I am considering to merge them before the MetaPhlAn2. However, I do not know I need to run bbmap first to do quality control, OR to run bbmerge first to merge the sequence. Any suggestions?

          Thanks in advance

          Comment


          • @chloe - It's normally simplest and most effective to do QC first on the raw data, then anything else (such as merging) later.

            @silask - they way you are doing it is currently the most effective way. It's a little bit annoying to have to run BBNorm twice, but that's the only way to process both paired and unpaired reads.

            Comment


            • Hi, Brian,

              Thanks for the reply. However, I have tried the QC. I used
              bbduk.sh in=R1.fastq.gz out=filter_R1.fq maq=30
              bbduk.sh in=R2.fastq.gz out=filter_R2.fq maq=30
              (no reads in R1R2 will be trimmed)

              bbduk.sh in=R1.fastq.gz out=clean_R1.fq trimq=30
              bbduk.sh in=R2.fastq.gz out=clean_R2.fq trimq=30
              (it will trim 50% of reverse reads, but no forward reads)

              bbduk.sh in1=R1.fastq.gz in2=R2.fastq.gz out1=R1_001.fq out2=R2.fq outm=fail.fq bhist=hist_base.txt qhist=hist_q.txt aqhist=hist_aq.txt bqhist=hist_bq.txt ecco=t
              (Also no reads will be trimmed)

              But when I run the code BBmerge, only 32.268% of the reads can be joined.

              Do you have any suggestions?

              Thanks in advance.

              Comment


              • @chloe1005: It is possible that only 32% of your reads have inserts of a size that the reads can merge.

                `trimq=30` is too severe a bar for trimming. If you have a reference genome then not doing any trimming for quality works fine. If you are doing any de novo work then you may want to trim at Q20 or Q25.

                Comment


                • Hi,
                  I am still confusing about the difference between the quality trimming and quality filtering. What is the difference between them?
                  May also know how to get the reference genome? Since I also see the first threads in this post.
                  Looking forward to getting the answer.

                  Comment


                  • Hi Brian, somehow the t=x flag doesn't reduce the number of nodes in use. Any suggestions what goes wrong or can I somehow include Java flags?
                    Bests,
                    Ulrike

                    Comment


                    • RQCFilter Norm and EC

                      Hi Brian,

                      I am trying to trim and filter my data with RQCFilter but I cannot find an option for normalisation and error correction. Are there any parameters in this package? Also there is a parameter called -merge. Does it do merging? Should I set it to false and try normalising and error correcting first?

                      Comment


                      • Can you clarify which program you are referring to? I don't think there is a RQCfilter program in BBMap suite.

                        Comment


                        • Source: https://jgi.doe.gov/data-and-tools/b...preprocessing/

                          "These steps replicate the QA protocol implemented at JGI for Illumina reads. There is a program “RQCFilter” which implements them as a pipeline, but that is not publically available because it has numerous hard-coded paths to reference datasets of contaminants."

                          It is in the bbtools files.

                          Nevermind! 1) Is it a good plan to normalise and error correct first BEFORE merging? 2) Do I need to follow a different approach at trimming and filtering short vs long mate pair reads (Nextera)?
                          Last edited by kokyriakidis; 07-08-2018, 12:15 PM.

                          Comment


                          • Since notes on the page you linked say this:
                            There is a program “RQCFilter” which implements them as a pipeline, but that is not publically available because it has numerous hard-coded paths to reference datasets of contaminants.
                            You should follow the steps that are denoted to replicate that functionality on the linked page.

                            In general @Brian has recommended merging reads before doing any additional manipulations.

                            Comment


                            • Originally posted by GenoMax View Post
                              Since notes on the page you linked say this:


                              You should follow the steps that are denoted to replicate that functionality on the linked page.

                              In general @Brian has recommended merging reads before doing any additional manipulations.
                              In long pair mate reads I just do the splitNextera extra step? Otherwise the pipeline remains the same?

                              Comment


                              • I would think so. I don't have first hand experience with mate pair reads but I recall that you need to switch one of the reads around.

                                Comment

                                Latest Articles

                                Collapse

                                • seqadmin
                                  Strategies for Sequencing Challenging Samples
                                  by seqadmin


                                  Despite advancements in sequencing platforms and related sample preparation technologies, certain sample types continue to present significant challenges that can compromise sequencing results. Pedro Echave, Senior Manager of the Global Business Segment at Revvity, explained that the success of a sequencing experiment ultimately depends on the amount and integrity of the nucleic acid template (RNA or DNA) obtained from a sample. “The better the quality of the nucleic acid isolated...
                                  03-22-2024, 06:39 AM
                                • seqadmin
                                  Techniques and Challenges in Conservation Genomics
                                  by seqadmin



                                  The field of conservation genomics centers on applying genomics technologies in support of conservation efforts and the preservation of biodiversity. This article features interviews with two researchers who showcase their innovative work and highlight the current state and future of conservation genomics.

                                  Avian Conservation
                                  Matthew DeSaix, a recent doctoral graduate from Kristen Ruegg’s lab at The University of Colorado, shared that most of his research...
                                  03-08-2024, 10:41 AM

                                ad_right_rmr

                                Collapse

                                News

                                Collapse

                                Topics Statistics Last Post
                                Started by seqadmin, Yesterday, 06:37 PM
                                0 responses
                                10 views
                                0 likes
                                Last Post seqadmin  
                                Started by seqadmin, Yesterday, 06:07 PM
                                0 responses
                                9 views
                                0 likes
                                Last Post seqadmin  
                                Started by seqadmin, 03-22-2024, 10:03 AM
                                0 responses
                                50 views
                                0 likes
                                Last Post seqadmin  
                                Started by seqadmin, 03-21-2024, 07:32 AM
                                0 responses
                                67 views
                                0 likes
                                Last Post seqadmin  
                                Working...
                                X