Hello !
I come to you because I have to help one of my colleague who is a plant biologist. The purpose of this study is to cluster 70 quantitative variables. Each of these variables represents a different protein (it is a measure done on it, I don't know how exactly it works).
But here is the difficulty :
We have n = 100 flowers, but we have another variable "drug". Indeed, 50 flowers have been "drugged" and the other 50 flowers have not (control group), and another variable "time", which allow us to follow the evolution in time of the presence of the 70 proteins (1 day, 7 days and 1 month).
Therefore, we need to cluster 70 quantitative variables but we have two conditions : the flower has a drug or not + a time effect.
Usually, it is quite easy to cluster variables : we use an agglomerative clustering based on the correlation between the variables, but if we add conditions on the data it is more complicated and I don't know how to proceed.
Thank you so much for your help (from France)
Bye !!
I come to you because I have to help one of my colleague who is a plant biologist. The purpose of this study is to cluster 70 quantitative variables. Each of these variables represents a different protein (it is a measure done on it, I don't know how exactly it works).
But here is the difficulty :
We have n = 100 flowers, but we have another variable "drug". Indeed, 50 flowers have been "drugged" and the other 50 flowers have not (control group), and another variable "time", which allow us to follow the evolution in time of the presence of the 70 proteins (1 day, 7 days and 1 month).
Therefore, we need to cluster 70 quantitative variables but we have two conditions : the flower has a drug or not + a time effect.
Usually, it is quite easy to cluster variables : we use an agglomerative clustering based on the correlation between the variables, but if we add conditions on the data it is more complicated and I don't know how to proceed.
Thank you so much for your help (from France)
Bye !!