R for biologists with Metagenomics 2600-OG-EN-RBM

Exercise 1
Installation of R and R Studio, Creating your first R script.
Exercise 2
Structure of functions with different number of arguments. Different data types
Exercise 3
Different objects in R: vector, matrix, array, list, data frame
Exercise 4
Creating project in R. Working with data frame
Exercise 5
Report Writing in R Markdown
Exercise 6
Creating function with R
Exercise 7
Case studies.
Exercise 8
Introduction to metagenomics. Matagenomics as a tool in the ecology of microorganisms. The importance of metagenomics and development perspectives.
Isolation of biological material for metagenomic analyzes. Methods and tools for DNA / RNA isolation. Requirements and quality of genetic material.
Exercise 9
Bioinformatics analysis used in NGS data processing.
Taxonomy analysis of microorganism communities. Numerous and rare OTUs, Venn diagrams. Ways to visualize data from taxonomy.
Exercise 10
Alpha diversity. Analysis of biodiversity of microorganism communities. Dilution curves, indicators of species richness (Sobs, Chao1, ACE).
Alpha diversity. Biodiversity indicators of microorganism communities (Shannon-Wiener index, Simpson index). Equivalence indicators.
Exercise 11
Beta diversity. Distance, similarity / similarity of communities. Cluster analysis.
Beta diversity. Consulting methods (PCA, PCoA).
Exercise 12
Beta diversity. Hypothesis testing (ANOSIM, SIMPER, PERMANOVA).
Other methods for visualizing data from NGS sequencing. Correlations and heatmaps.
Exercise 13
Genome sequencing
Use of genome information to identify microorganisms (ANI, in silico DDH).
Genomic annotation in Rast Server. The role of microorganisms in the environment.
Exercise 14, 15
Students' own work. Development of analysis results, report preparation and presentation of conclusions.