Bioinformatics and Computational Biology

Recent methodological advances in molecular biology and genetics have led to a significant increase in the volumes of available data, allowing previously impossible studies on biodiversity and evolution. However, exploiting this enormous amount of information requires knowing how to handle some basic statistical and informatic tools. This course will provide a comprehensive introduction to R, a widely used programming language for statistical computing and graphics, with a focus on simple statistical methodologies of immediate relevance to studies on biodiversity and evolution. Students will learn to install R Studio (the R graphical interface), perform basic statistical tests (average comparison, linear regressions, etc.) and prepare graphs. The course will also include a case study on the analysis of environmental DNA (eDNA) sequencing data to study microbial diversity.

The course aims to provide students with: i) an introduction to the application of bioinformatics in evolutionary and ecological studies; ii) ability to manage and analyze data using R; iii) the development of skills in choosing and carrying out basic statistical analyses; iv) the ability to prepare high-quality graphs in R, such as heatmaps and Principal Component Analysis (PCA). Furthermore, the course aims to stimulate the student to develop their IT/statistical skills also in the rest of their university and post-university growth path, through the exploration of the myriad of R packages available.