Producing Dose Response Curves in R

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  • Опубликовано: 8 фев 2025
  • In this tutorial we will work through the entire process of performing a dose response curve analysis in R. We start by importing, cleaning and reformatting the data. We then do some initial plotting and exploration. After adding some normalisation to the data we perform the curve fitting and then check the model to ensure that it matches the data well.

Комментарии • 15

  • @Mrkiwidude1
    @Mrkiwidude1 8 месяцев назад +1

    Really thorough explanation. When I followed it step for step, it worked for me. Thank you!

  • @david_noe
    @david_noe Год назад

    This is a fantastic explanation. Thank you!

  • @happylearning-gp
    @happylearning-gp Год назад

    Excellent tutorial, Thank you very much

  • @MariaJoseMolinaQuesada-oi1gx
    @MariaJoseMolinaQuesada-oi1gx 10 месяцев назад

    Perfect explanation, thank you very much for this video!

  • @ibrahimlawan9663
    @ibrahimlawan9663 11 месяцев назад +1

    This is an excellent tutorial. Can one use glm (binomial family) instead to determine EC50 or LC50, as the case may be?

  • @苏峰-p6v
    @苏峰-p6v Год назад

    thanks for your explanation

  • @oliverpiercey7200
    @oliverpiercey7200 4 месяца назад

    Can I please ask, how do you determine the dose that corresponds to IC10 or IC20 etc?

  • @VinithaNanjappa
    @VinithaNanjappa Год назад

    I am getting an error for the predict model. Could you please help?

  • @juanpdiddy
    @juanpdiddy 8 месяцев назад

    one last thing, anyone knows how to add error bars to the final plot? When I try to add the error bars by combining the earlier plot I get Error in geom_line(data = predicted_data, aes(x = dose, y = prediction)) :

    • @juanpdiddy
      @juanpdiddy 8 месяцев назад

      here is an answer I came up with
      ```{r}
      drc_per_condition %>%
      ggplot(aes(x=Dose, y=response, colour=condition))+
      geom_point()+
      geom_errorbar(aes(ymin=response-sem, ymax=response+sem), width=.2) +
      scale_x_log10() +
      geom_line(
      data=predicted_data,
      aes(x=dose, y=prediction)
      )
      ```

  • @soniakhan9472
    @soniakhan9472 8 месяцев назад

    What if you want error bars on the final curve?

    • @juanpdiddy
      @juanpdiddy 8 месяцев назад

      Did you figure this out? I tried but can’t. Keep getting an error

    • @soniakhan9472
      @soniakhan9472 8 месяцев назад

      @@juanpdiddy not yet, sorry

    • @juanpdiddy
      @juanpdiddy 8 месяцев назад

      @@soniakhan9472 Thanks, it seems like adding ymin and ymax like in an earlier plot should work but I keep getting an error that response is not found yet if I don't have ymin or ymax in the expression, it finds response just fine...so annoying.

    • @juanpdiddy
      @juanpdiddy 8 месяцев назад

      @@soniakhan9472 I figured it out. The problem was due to coloring, aestetics for some reason. The following chuck, does the curve fitting and adds error bars to the final plot. Hope it works for you.
      ```{r}
      drc_per_condition %>%
      ggplot(aes(x=Dose, y=response, colour=condition))+
      geom_point()+
      geom_errorbar(aes(ymin=response-sem, ymax=response+sem), width=.2) +
      scale_x_log10() +
      geom_line(
      data=predicted_data,
      aes(x=dose, y=prediction)
      )
      ```