R. Sanges, 35 hours

Title: Genomics and Transcriptomics Data Analysis and Mining

Teacher: Prof. Sanges

Amount of frontal teaching: 35 hours

Description: The course is an introduction to the experimental design and the data analysis and mining in Genomics made by a mixture of theoretical lessons and practical sessions. Students will also be instructed on the history of molecular biology and the milestones that lead to the sequencing of the human genome and the development of current functional genomics strategies and theories. Evolutionary aspects and the contribution of non-coding RNA and transposons to the evolution of complexity and the impact of their activity in the brain will be discussed. The course is an open discussion between the teacher and the students.

Specific covered topics are:

1. Cells, genomes, genes and the Central Dogma of molecular biology.

2. Transcription, transposons, non-coding and the evolution of organismal complexity.

3. Transposons and the brain.

4. Bioinformatics databases and tools.

5. Good practices for experimental design.

6. Transcriptome mining and meta analysis with gene expression data.

7. R for dummies.

8. Data exploration and visualization.

9. False discovery rate.

Theoretical lectures

• Cells, genomes, genes and the Central Dogma

• The definition of an eukariotic gene is an evolving concept

• Transcription, transposons, non-coding and the evolution of organismal complexity

• Bioinformatics databases and tools

• Simple sequences handling and mining using public web databases and tools

• Good practices for experimental design

• Transcriptome mining and meta analysis with gene expression data

• Transposons and the brain

Practical sessions

• R for dummies

• Variables: scalars, vectors, lists, matrices, data-frames, operators

• Data exploration and selection: operators and operations, distributions, correlations, boxplots, histograms, xyplots, subsetting, filtering, t-test, multiple hypothesis testing, p-value correction and false discovery rate

• Input/output: text file import, data-frame export, chart export

• Extracting and analyzing molecular data using genome browsers and public genomic databases and tools