EPPN2020 Training: Experimental design and statistical analysis of phenotyping platform experiments
This course will discuss criteria for choosing a suitable experimental design for phenotyping experiments. Subsequently we will show options for analysing features extracted from phenotyping platforms.
High throughput phenotyping platforms allow analysis of the genetic variability of traits at several scales of plant organization under contrasting and well-defined environmental scenarios.
After that a large number of platforms has been built, the priority now is to design methods for the analysis of heterogeneous datasets involving thousands/millions of data points, contrasting environmental conditions and tens/hundreds of measured traits. This course will firstly discuss criteria for choosing a suitable experimental design for phenotyping experiments. Subsequently we will show options for analysing features extracted from phenotyping platforms with a focus on spatial and longitudinal modelling (in R). We aim at increasing the precision of estimation new phenotypic traits and parameters thereby facilitating the combined analysis of data from multiple scales and platforms.
The training course is free but registration is mandatory and should be made through the following online form:
Please note that the number of places is limited so we will apply the "first come, first served" rule!
For further information please check the training programme:
EPPN2020 Training (PDF)