Seqanswers Leaderboard Ad

Collapse

Announcement

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

  • Organizing projects, data inputs and output

    Hello!

    Do you have any suggestions, pointers, references, models on how to organize projects and their correspondingraw data, rmarkdowns, results, etc?

    We do a lot of bioinformatics projects, most of them have as raw data, fastq files, alignments files, differential expression counts matrices, etc; we develop some kind of pipeline and data processing and as output have some kind of report that we generate, as well as output data. We need to organize this information so that we can answer for example:

    - What have we done for investigator X?
    - When was the last time that we did such and such analysis?
    - What was the output for the analysis we did for investigator X or project Y?
    - I need the output for project Y again.
    - For whom have we done type of analysis Z (e.g. Differential expression, etc.)
    - Project X that we did in 2010, what did it consist of? what was the input raw data, and output?

    And other things like this. Right now, for answering some of these things I basically do a very crude search on the directory tree, which is getting bigger and bigger, and rely on memory, past emails, etc. Dangerous.

    Any suggestions? Including any commercial software for helping with these kinds of things?

    Thanks,
    Ramiro

  • #2
    Ramiro, you're gonna need a query-able database. If MySql is not on your favorites list, Microsoft Access has a business template that can be hacked to run a core facility. It's a pain to transfer old data, but it'll work for most of the things you've asked about. My suggestion is to do as much as possible using dates in the yyyymmdd format for starting projects.

    Comment

    Latest Articles

    Collapse

    • seqadmin
      Current Approaches to Protein Sequencing
      by seqadmin


      Proteins are often described as the workhorses of the cell, and identifying their sequences is key to understanding their role in biological processes and disease. Currently, the most common technique used to determine protein sequences is mass spectrometry. While still a valuable tool, mass spectrometry faces several limitations and requires a highly experienced scientist familiar with the equipment to operate it. Additionally, other proteomic methods, like affinity assays, are constrained...
      04-04-2024, 04:25 PM
    • 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

    ad_right_rmr

    Collapse

    News

    Collapse

    Topics Statistics Last Post
    Started by seqadmin, 04-11-2024, 12:08 PM
    0 responses
    18 views
    0 likes
    Last Post seqadmin  
    Started by seqadmin, 04-10-2024, 10:19 PM
    0 responses
    22 views
    0 likes
    Last Post seqadmin  
    Started by seqadmin, 04-10-2024, 09:21 AM
    0 responses
    17 views
    0 likes
    Last Post seqadmin  
    Started by seqadmin, 04-04-2024, 09:00 AM
    0 responses
    49 views
    0 likes
    Last Post seqadmin  
    Working...
    X