Unconfigured Ad

Collapse
X
 
  • Time
  • Show
Clear All
new posts
  • chobeich
    Junior Member
    • Jan 2020
    • 5

    #1

    SNP array analysis

    I there!!

    A friend has passed me the data of an Infinium Omni5-4 array. In short, they have applied two different mutagens to a cell line. I have passed a data set that contains:
    3 mother samples (MS)
    3 samples mutagen 1 (M1)
    3 samples mutagen 2 (M2)
    Its objective is to identify the mutagenic potential of each mutagen.
    After googeling, I think what I need to do is a Manhattan plot to identify the chromosomal regions that have mutated the most for each mutagen.
    What I have done at the moment is:
    1 Genotyping callin, using the Genotyping Module of Genome Studio
    2 Establish the reference set: SNP's 100% call and with the same genotype in all MS.
    3 Assign each SNP of samples M1 and M2 a 1 if the genotype has varied from the reference or a 0 if it has not. The SNPs of the M1 and M2 samples that are not in the reference set or that are not 100% called have been discarded.
    I have done all this with perl. What I now have is a text file with the following structure:
    SNP_1 SNP_2 ...
    M1.1 1 0
    M1.2 1 1
    .
    .
    M2.3 1 0

    And that's all folks!!, I have no idea what I should do now.
    Any help will be welcome because, as you may deduced, I have no idea of working with arrays or statistics.
    Thank you
  • chobeich
    Junior Member
    • Jan 2020
    • 5

    #2
    Hi Vasudev,
    I'm afraid this is not an array analysis, at least not complete.
    The part of the analysis of results, that I hope someday someone completes, is missing.
    In addition, until someone with experience in the analysis of arrays is pronounced, this should be interpreted as a noob's attempt to interpret data with which he had never worked before.
    Anyway, thanks for your comment.

    Comment

    Latest Articles

    Collapse

    • SEQadmin2
      Multiomic Liquid Biopsy: What DNA/RNA Panels Reveal That DNA Alone Can’t
      by SEQadmin2



      Tumors contain complex mixtures of cell populations that evolve in response to treatment and host-specific factors. Tissue biopsies provide only static snapshots of a tumor’s state. But what if we could follow that evolution over time using a minimally invasive technique?

      Liquid biopsies can detect tumor-derived material circulating in the bloodstream, providing a way to study treatment response, detect emerging resistance, and discover new biomarkers. Circulating
      ...
      10-14-2026, 09:55 AM
    • SEQadmin2
      New Genomics Technologies Take Aim at Long-Standing Limits
      by SEQadmin2


      Researchers using sequencing and genomics tools often have to make trade-offs. They can choose between speed or scale, short reads or long-range information, or targeted panels or a view of the whole transcriptome. New technologies that have been released this year are built to address those tough choices.

      We asked six companies the same four questions to learn about their latest products. The new technologies bring a lot to the table, including rethinking sequencing
      ...
      09-28-2026, 10:25 AM

    ad_right_rmr

    Collapse

    News

    Collapse

    Topics Statistics Last Post
    Started by SEQadmin2, 10-22-2026, 11:13 AM
    0 responses
    27 views
    0 reactions
    Last Post SEQadmin2  
    Started by SEQadmin2, 10-22-2026, 10:48 AM
    0 responses
    20 views
    0 reactions
    Last Post SEQadmin2  
    Started by SEQadmin2, 10-15-2026, 10:52 AM
    0 responses
    36 views
    0 reactions
    Last Post SEQadmin2  
    Started by SEQadmin2, 10-14-2026, 05:39 AM
    0 responses
    43 views
    0 reactions
    Last Post SEQadmin2  
    Working...