Learning Outcomes
Upon successful completion of the course, students will:
1) understand and process DNA sequencing data from different next-generation DNA sequencing platforms
2) become familiar with the most common next-generation DNA sequencing protocols
3) be able to analyze transcriptome, ddRAD and barcoding expression data
4) be able to perform statistical analysis of molecular pathways and gene ontologies in gene lists
5) become familiar with the above analyses in R, python and UNIX/Linux environments.
Course Content (Syllabus)
Course contents include: 1) introduction to the nature and processing of DNA sequencing data (e.g. (a) the nature and processing of DNA sequencing data (e.g., filtering) from various next-generation DNA sequencing platforms; 2) theory and practical exercises on the most popular next-generation DNA sequencing protocols such as (a) hybrid sequencing of small and medium size whole genomes, (b) transcriptome synthesis, quantification, and expression analysis, (c) ddRAD, and (d) eDNA and barcoding, 3) gene characterization and statistical analysis of molecular pathways and gene ontologies in gene lists. A significant part of the practical exercises will be performed in R, python and UNIX/Linux environments.