Seqanswers Leaderboard Ad

Collapse

Announcement

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

  • 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

  • #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

    • 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...
      Today, 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, 08:18 AM
    0 responses
    10 views
    0 likes
    Last Post seqadmin  
    Started by seqadmin, Today, 08:04 AM
    0 responses
    12 views
    0 likes
    Last Post seqadmin  
    Started by seqadmin, 06-03-2024, 06:55 AM
    0 responses
    13 views
    0 likes
    Last Post seqadmin  
    Started by seqadmin, 05-30-2024, 03:16 PM
    0 responses
    27 views
    0 likes
    Last Post seqadmin  
    Working...
    X