Seqanswers Leaderboard Ad

Collapse

Announcement

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

  • Data format - Unusable to R and Plink

    Hullo! Apologies for the seemingly basic question but I am in knots over this and hope there is some help.

    I have recently 'inherited' an Illumina dataset containing about 36,000SNP genotypes for about 400 individuals. The data I have is presented as a 3 columns in a text file.

    The columns are 'Indiv_ID', 'SNP_ID' and 'Genotype' (so 36000x400 rows in total) and I need the data in some usable format so that I can extract data for specific 500 SNPs. ideally I would prefer the data in an individual x SNP matrix.

    Usually I have used R to reshape such data as such but this file seems to be too big and it just freezes whilst processing. I have also used Plink in the past to extract specific SNP data from 'column' data but in the text file I have, the genotype is given as an 'AB' format which Plink doesn't accept as a compound genotype. I have attempted to change all As and Bs for 1s and 2s so that I can input as a compound to Plink, but the software I was using to do this also adds " "s which then need to be removed. And no text editor I have seems to cope with this for so many lines of text.

    I am not able to get this data in any other format and the only other data I have in relation to this is (just) enough for me to creat a .map file for Plink. Otherwise it is just the (seeminly) infinite column. I appreciate that this is probably a very simple task all in but at the moment I cannot see the wood for trees, and am going around in circles. I would welcome any starting points or good reference sites to check out!

    Thanks!

  • #2
    Just write the names of the SNP_IDs that you're interested to a file and either use grep to get them out or just write a small python/perl/whatever script to do so.

    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