Seqanswers Leaderboard Ad

Collapse

Announcement

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

  • bbduk for mirna mapping

    Hi,
    I have run a miseq run for microrna detection, filtered the data (removed adaptors and ncRNAs (others than microRNAs) and i´m now going to identify reads mapping to microRNAs in Human.

    As for the strategy not sure if i have to map to the human genome or i can directly map to the mature.fa database from mirbase. Any suggestion ? The reason i have choosen not to map to the human genome is that not really interested in denovo microRNAS but on the contrary i´m not sure if i have first to remove reads that can map to other parts of the genome.

    So far i have decided to align to mature mirbase database.

    I´m using the following command:

    bbduk.sh ref=mature.fa.gz in=1.fa.gz stats=statsmature.txt out=mirna.fa hdist=0


    1/ What is the best approach to identify full match microRNAs (no mismatch) with bbduk.
    2/ How to identify isomirs ? Do i need to cluster reads first with vsearch with a 99% identity and then map to mirbase with 100% full match.

    Thanks for your comments

  • #2
    By default BBDuk will allow one mismatch of the middle base in a kmer (even with "hdist=0"). You need to add the flag "mm=f" to require exact matches. mm stands for "maskmiddle".

    If you want to require every kmer in a sequence to also be present in the reference, you can also add "mkf=1" (which stands for min kmer fraction). That will make the process completely intolerant of any errors or remaining adapter sequence, though.

    Be sure to specify a kmer length. If you are looking for RNAs as short as 17bp, then set "k=17"; the default is much longer.

    So, the full command might look like:

    Code:
    bbduk.sh ref=mature.fa.gz in=1.fa.gz stats=statsmature.txt out=mirna.fa hdist=0 [B]mm=f mkf=1 k=17[/B]
    ...but you should determine for yourself what value you want for K.

    Comment

    Latest Articles

    Collapse

    • seqadmin
      Best Practices for Single-Cell Sequencing Analysis
      by seqadmin



      While isolating and preparing single cells for sequencing was historically the bottleneck, recent technological advancements have shifted the challenge to data analysis. This highlights the rapidly evolving nature of single-cell sequencing. The inherent complexity of single-cell analysis has intensified with the surge in data volume and the incorporation of diverse and more complex datasets. This article explores the challenges in analysis, examines common pitfalls, offers...
      Yesterday, 07:15 AM
    • seqadmin
      Latest Developments in Precision Medicine
      by seqadmin



      Technological advances have led to drastic improvements in the field of precision medicine, enabling more personalized approaches to treatment. This article explores four leading groups that are overcoming many of the challenges of genomic profiling and precision medicine through their innovative platforms and technologies.

      Somatic Genomics
      “We have such a tremendous amount of genetic diversity that exists within each of us, and not just between us as individuals,”...
      05-24-2024, 01:16 PM

    ad_right_rmr

    Collapse

    News

    Collapse

    Topics Statistics Last Post
    Started by seqadmin, Today, 06:58 AM
    0 responses
    8 views
    0 likes
    Last Post seqadmin  
    Started by seqadmin, Yesterday, 08:18 AM
    0 responses
    15 views
    0 likes
    Last Post seqadmin  
    Started by seqadmin, Yesterday, 08:04 AM
    0 responses
    15 views
    0 likes
    Last Post seqadmin  
    Started by seqadmin, 06-03-2024, 06:55 AM
    0 responses
    13 views
    0 likes
    Last Post seqadmin  
    Working...
    X