Multivariate data analysis with R and vegan

Dates

21-25 November 2022

 

Due to the COVID-19 outbreak, this course will be held online

 

Course overview

The R statistical language has enjoyed wide and rapid adoption by many researchers, and is used across many ecological subdisciplines for statistical analyses and the production of publication-quality figures. For community ecologists using R, one of the most-used, and useful, add-on packages is vegan, which provides a wide range of functionality covering inter alia ordination, diversity analysis, and ecological simulation. This workshop will offer participants a practical introduction to some of the most useful functions available within vegan. We will focus on the use of ordination methods and on the use of restricted permutations to test a range of experimental designs.
We will focus in particular on when and how to use multivariate methods including unconstrained and constrained ordination (CCA, RDA, Constrained PCoA), as well as between-group tests such as PERMANOVA. We will cover concepts such as design- and model-based permutations and the exchangeability of samples in tests. We will also discuss the use of vegan to go beyond simply fitting a constrained ordination model, to diagnostics, plotting, etc.

 

 

Target audience and assumed background

This course is suitable for PhD students (including senior thesis-based masters students) and researchers working with multivariate data sets in biology (inter alia ecology, animal science agriculture, microbial ecology/microbiology), with limited statistical knowledge but a willingness to learn more.
Participants should be familiar with RStudio and have some fluency in programming R code, including being able to import, manipulate (e.g. modify variables) and visualise data. There will be a mix of lectures, and hands-on practical exercises throughout the course.

 

Learning outcomes

1.    Have a good introductory understanding of the main approaches used in the analysis of multivariate data sets
2.    Be be able to choose an appropriate method to use to analyse a data set
3.    Understand how to use restricted permutation tests with constrained ordination methods to test the effects of predictor variables or experimental treatments
4.    Be able to use the R statistical software to analyse multivariate data

Program

Sessions from 14:00 to 20:00 (Monday to Thursday), 14:00 to 19:00 on Friday (Berlin time). From Tuesday to Friday, the first hour will be dedicated to Q&A and working through practical exercises or students’ own analyses over Slack and Zoom. Sessions will interweave mix lectures, in-class discussion/ Q&A, and practical exercises.

 

Monday– Classes from 2-8 PM Berlin time


An introduction to multivariate data and their analysis.
Dissimilarity and dissimilarity coefficients
Diversity metrics
Transformations (e.g. for high-throughput biological data)


Tuesday– Classes from 2-8 PM Berlin time


Unconstrained ordination


•    Principal Components Analysis
•    Correspondence Analysis
•    Principal Coordinates Analysis
•    Non/metric Multidimensional Analysis (NMDS)



Wednesday– Classes from 2-8 PM Berlin time

Constrained Ordination


•    Redundancy Analysis
•    Canonical Correspondence Analysis
•    Distance-based Redundancy Analysis
•    PERMANOVA (adonis()) and PERMDISP (betadisper())


Thursday– Classes from 2-8 PM Berlin time


Statistical inference for ordination models


•    Statistical testing with permutation tests
•    Restricted permutation tests



Friday– Classes from 2-7 PM Berlin time

 

Extended practical examples

 

 

 

 


Cost overview

 

Package 1

 

                      480 €


Should you have any further questions, please send an email to info@physalia-courses.org

Cancellation Policy:

 

> 30  days before the start date = 30% cancellation fee

< 30 days before the start date= No Refund.

 

Physalia-courses cannot be held responsible for any travel fees, accommodation or other expenses incurred to you as a result of the cancellation.