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  • GenoMax
    replied
    Options for verifying phred+33 format: https://www.biostars.org/p/63225/

    If your dataset is already sanger format then in galaxy it is possible to assign ".fastqsanger" type to this data avoiding the grooming step.

    Leave a comment:


  • hyates
    replied
    Originally posted by GenoMax View Post
    As long as you know the reads are in sanger format (phred+33) you can go on to trimming/filtering.
    Okay, my background is not biology and I am in computer science. So maybe you can answer this to me because the person who did this isn't here anymore.
    1. It seems the data is 100 cycle SE from high output: 1 lane (Illumina HiSeq 2500)
    2. They did trimming from sanger to sanger data?
    3. How can I verify myself that this is phred+33 format?


    Did they make a mistake in grooming? It seems to me that Illumina HiSeq fastq data is not sanger? Or am I totally n00b?

    Leave a comment:


  • hyates
    replied
    Originally posted by GenoMax View Post
    You can get the code galaxy uses here (individual tools likely have other dependencies and it may not be simple to run them on the command line): https://toolshed.g2.bx.psu.edu/repos/devteam

    As long as you know the reads are in sanger format (phred+33) you can go on to trimming/filtering.
    That's a great place to look. It would be nice if the tools had a readme.txt for dependencies, but I read whatever docs I can find first. If that doesn't work, I can always reach out again.

    That being said, thank you so much Geno. You've been a lot of help and I want you to know this. Have a great day.

    Leave a comment:


  • GenoMax
    replied
    You can get the code galaxy uses here (individual tools likely have other dependencies and it may not be simple to run them on the command line): https://toolshed.g2.bx.psu.edu/repos/devteam

    As long as you know the reads are in sanger format (phred+33) you can go on to trimming/filtering.

    Leave a comment:


  • hyates
    replied
    Originally posted by GenoMax View Post
    There is no need to "groom" if your reads are already in sanger format.
    I am reading these notes and trying to duplicate the results. It states they used galaxy and the first step in the cleaning process was grooming. Specifically,
    Groomed 28403332 sanger reads into sanger reads
    They then trimmed and then filtered the results. So what I should really be doing is focusing on the trimming and filtering, yes?

    If so, my question is how can I obtain the tools galaxy uses for trim and filter for local commandline processing? Thank you for your patience and prompt answer.

    Leave a comment:


  • GenoMax
    replied
    There is no need to "groom" if your reads are already in sanger format.

    Leave a comment:


  • How to perform grooming that galaxy does but on the commandline?

    How do I groom sanger reads into sanger reads on my local commandline using the same tool that galaxy has found here?

    In other words, I would like to do the following:
    • Obtain the same tool galaxy uses for grooming locally
    • Invoke this tool on my local commandline
    • Figure out how to use this tool on an entire directory of fastq files


    I of course went to galaxy and I only saw a reference to a paper, but I don't know where to obtain the tool?

    Thank you very much for reading this post.

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