Gene Expression Analysis using PCA in R

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  • Опубликовано: 13 дек 2024
  • Multivariate Analysis: Gene Expression Analysis using PCA in R
    R code in kaggle: www.kaggle.com...
    R is a free software environment for statistical computing and graphics, and is widely used by both academia and industry. R software works on both Windows and Mac-OS. It was ranked no. 1 in a KDnuggets poll on top languages for analytics, data mining, and data science. RStudio is a user friendly environment for R that has become popular.

Комментарии • 41

  • @vikiviky1122
    @vikiviky1122 2 года назад +1

    Most underrated channel.. he has amazing way of communicating the key things

    • @bkrai
      @bkrai  2 года назад

      Thanks for comments!

  • @Tounesna2012
    @Tounesna2012 3 года назад +1

    Glad to see you back.

    • @bkrai
      @bkrai  3 года назад

      Thanks!

  • @nasrmhm
    @nasrmhm 2 года назад +1

    Thanks Dr.Bharatendra

    • @bkrai
      @bkrai  2 года назад

      You are welcome!

  • @ritagutierrezgonzalez8400
    @ritagutierrezgonzalez8400 3 года назад +1

    Brilliant content, nice to see you back Sir

    • @bkrai
      @bkrai  3 года назад

      Thanks!

  • @jainaik3035
    @jainaik3035 3 года назад +1

    Sir, thank you so much for explaining such a complex concept in a very very simple manner.

    • @bkrai
      @bkrai  3 года назад

      You are most welcome!

  • @pkmitrabotany
    @pkmitrabotany 3 года назад +2

    Your channel is a gold mine sir, please keep making videos 🙏😍❤️

    • @bkrai
      @bkrai  3 года назад

      Thanks for comments!

  • @jaiganeshc9417
    @jaiganeshc9417 3 года назад +1

    Nice explanation Sir ! 👍

    • @bkrai
      @bkrai  3 года назад

      Thanks!

  • @glivec
    @glivec 3 года назад +1

    Really good! Looking forward to a lesson about t-SNE clustering analysis

    • @bkrai
      @bkrai  3 года назад +1

      Great suggestion!

  • @saminba9111
    @saminba9111 3 года назад +1

    Dear Professor,
    Do you have any recorded video about Multinomial logit: estimation on a subset of alternatives in R? estimation multinomial logit when alternatives are large number,
    could you here add the link?

    • @bkrai
      @bkrai  3 года назад +1

      Here is the link:
      ruclips.net/video/S2rZp4L_nXo/видео.html

    • @saminba9111
      @saminba9111 3 года назад +1

      @@bkrai when the alternatives are large and we want to estimate on the subset,is there any embedded function in R?

    • @bkrai
      @bkrai  3 года назад

      By alternatives do you mean number of levels for the response?

    • @saminba9111
      @saminba9111 3 года назад

      ​@@bkrai yes, for example, the number of alternatives that the decision-maker or household have to choose between 120 different types and vintage of vehicles; when they have three vehicles they can choose between 120*120*120; i want to know how can i estimate on a subset of these choices in R when apply MNL model?

    • @saminba9111
      @saminba9111 3 года назад

      @@bkrai yes,for example, decision-maker choose between 120 different makes and models of vehicles,if the household has 4 vehicles, they cheese between 120*120*120*120, how can I in R estimate on a subset of these 120*120*120*120 instead to have a less complicated model?

  • @rishijadhav3984
    @rishijadhav3984 3 года назад +1

    Sir! You are awesome. I learned a lot from your videos.

    • @bkrai
      @bkrai  3 года назад

      Thanks for comments!

  • @victoriariosvazquez2924
    @victoriariosvazquez2924 2 года назад +1

    thank you!! keep up the great work :)

    • @bkrai
      @bkrai  2 года назад

      You are welcome!

  • @dimplekashyap1
    @dimplekashyap1 3 года назад +1

    Nice👌🏼

    • @bkrai
      @bkrai  3 года назад

      Thanks!

  • @killa14108
    @killa14108 2 года назад

    I still don't understand why the number of PCs stopped at 64. Shouldn't it stop at 6830 ? Isn't 64 the number of rows (samples) and not columns (variables)? Also, how can you determine the number of PCs to use for predictive models if all the PCs are contributing so little to the variance (like in this video)? Thanks!

  • @shuvhamdigitalacademy3228
    @shuvhamdigitalacademy3228 3 года назад +1

    Thank You Sir.

    • @bkrai
      @bkrai  3 года назад

      You are welcome!

  • @KN-tx7sd
    @KN-tx7sd 3 года назад +1

    Sir, many thanks. Can we include the PCA (significant components ) as covariates in a regression model, if so should they be included independent of other variables or in combination with other variables.

    • @bkrai
      @bkrai  3 года назад

      Yes you can do that. Here is an example:
      ruclips.net/video/OowGKNgdowA/видео.html

  • @nielsvandervelden3063
    @nielsvandervelden3063 3 года назад +1

    Great tutorials! Do you think you would get even better results if you perform a Boruta feature selection step first followed by PCA?

    • @bkrai
      @bkrai  2 года назад

      For data that I've used, it did provide better results.

  • @thalaramji3777
    @thalaramji3777 3 года назад +1

    Nice sir, 👍

    • @bkrai
      @bkrai  3 года назад

      Thanks!

    • @thalaramji3777
      @thalaramji3777 3 года назад

      @@bkrai gud mrg sir, in the next video, can you explain about the exploratory factor analysis and Conformatory factor analysis sir.

  • @Dr.munna89
    @Dr.munna89 3 года назад

    Sir waiting for EKC model in R, please

  • @biswajitdas2999
    @biswajitdas2999 3 года назад +2

    SIR plz stay in r

    • @bkrai
      @bkrai  3 года назад +1

      Yes, I’ll continue to work in R. 😊