MIT Deep Learning in Genomics - Lecture 16 - Genetics 1: GWAS, Linkage, Fine-Mapping

Поделиться
HTML-код
  • Опубликовано: 5 ноя 2024

Комментарии • 6

  • @fuma9532
    @fuma9532 2 месяца назад

    Brilliant lecture: I particularly enjoyed the first half, when SNPs, indels, STRs and such were explained (alongside the difference between Linkage Analysis and GWAS in scope and function), and the grand finale, the case study of actually going from GWAS to finding the causal mechanism in living beings was extremely exciting!
    I think being online may have hindered a few questions, as I had a few myself, and when students were asked to raise their hands many were often shaky, as if to indicate "not quite", but that could be just me projecting due to my lack of familiarity with the topic. Thank you so much for sharing this!

  • @chloecan8867
    @chloecan8867 4 года назад

    Hello, really enjoyed the video, thanks. I was just wondering, am I the only one who sees some errors in the Chi Square expected frequency calculations? They're only slightly off, but perhaps there was a reason for that?

  • @abhishekprajapat415
    @abhishekprajapat415 4 года назад

    So, Darwin basically said that put all the features in training and no feature selection but do one thing, While training do regularisation like hell.
    and Bingo you have the best model.

  • @chenwang8187
    @chenwang8187 2 года назад

    Nice video~ learned a lot

  • @shichengguo8064
    @shichengguo8064 4 года назад

    It would be great if the statistics for linkage analysis is explained.

    • @ManolisKellis1
      @ManolisKellis1  4 года назад +1

      See my lecture on population genomics here ruclips.net/video/ijqLhONYyhM/видео.html