Unconfigured Ad

Collapse
X
 
  • Filter
  • Time
  • Show
Clear All
new posts
  • sklages
    Senior Member
    • May 2008
    • 628

    GALAXY: Huge amount of data?

    Hi all,

    I have a (probably) very naive question ..

    We are running a few machines here as a core facility (Hiseq2000, GAIIx, 454tit,SOLiD) ... there are a couple of users interested in the capabilities of GALAXY, so I am thinking about a local install of the whole package.

    My concern is the data amount. E.g. one Hiseq2000 lane with a PE whole exome lib is roughly 2x20G (unzipped) fastq. I can definitively reduce the amount by zipping the datasets. But this is still a huge amount of data to be uploaded via Browser ...
    How is this working in practice if you have more than one lane?
    How are the jobs scheduled?

    I probably need to read more en detail before starting to set up my own installation ...

    thanks for any comment ..

    cheers,
    Sven
  • maubp
    Peter (Biopython etc)
    • Jul 2009
    • 1544

    #2
    Regarding the upload problem: Galaxy can be setup to let users upload their files by FTP, however, in your situation as a core facility you can import the files directly into Galaxy from disk. People do this as part of an automatic sequencing service pipeline - have a search on the Galaxy mailing list.

    Regarding the general data volume problem: Galaxy by default keeps all the files on disk, and you can have cron jobs to clean up "deleted" datasets. Some users on the Galaxy mailing list have reported needing to be more aggressive on their server to avoid running out of space.

    Comment

    Latest Articles

    Collapse

    • 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
    • SEQadmin2
      Nine Things a Sample Prep Scientist Thinks About Before Sequencing
      by SEQadmin2


      I’m not a sequencing expert. I’m a purification scientist who uses NGS to evaluate workflows my group develops. With this perspective, we think about the sample first and the NGS workflow second. The sequencer is an exceptionally honest reporter, but it can only report on what you give it, so whether you get clean, interpretable data from an NGS workflow is largely determined before you begin.

      Here are nine questions we think about, in roughly the order they matter, before...
      06-18-2026, 07:11 AM

    ad_right_rmr

    Collapse

    News

    Collapse

    Topics Statistics Last Post
    Started by SEQadmin2, 07-02-2026, 11:08 AM
    0 responses
    12 views
    0 reactions
    Last Post SEQadmin2  
    Started by SEQadmin2, 06-30-2026, 05:37 AM
    0 responses
    14 views
    0 reactions
    Last Post SEQadmin2  
    Started by SEQadmin2, 06-26-2026, 11:10 AM
    0 responses
    20 views
    0 reactions
    Last Post SEQadmin2  
    Started by SEQadmin2, 06-17-2026, 06:09 AM
    0 responses
    54 views
    0 reactions
    Last Post SEQadmin2  
    Working...