This page contains the information and materials of the OMICS workshop.

The idea of this workshop is to make the students familiar with the basic tools to perform different OMICS analyses. We will start with a general introduction to Python and R allowing the students to write their own programs for their analyses. Additionally we will provide an overview over existing programs in the area of differential expression and orthology detection.

Part 1: Linux and Python (20-24.11)

Responsible: Elias Dohmen, Carsten Kemena

Day Lecture Short Description Exercise Data (needed for Exercises) Materials
1 Linux Introduction Introduction to basic Linux commands Exercise
Solutions
Data
2 Python 1 Basics of programming in Python (variables, loops, compare basic conditions) Exercise
3 Python 2 Strings and functions are introduced and how they are used to read/write from/to files Exercise
4 Python 3 Further important pre-existing data types like dict, set etc. are introduced Exercise Data 
5 Python 4 ErrorHandling and modules from the standard library are introduced Exercise Data

Part 2: Statistics and Visualization in R (27-28.11)

Responsible: Evelien Jongepier

Requirements: Basic stats knowledge

Day Lecture Short Description Exercise Data (needed for Exercises) Materials
6 R basics lecture R syntax and data types R basics exercises
7 R plots lecture R data analyses and visualization R plots exercises GEOdata

Part 3: Transcriptomics (29-30.11)

Responsible: Evelien Jongepier

Requirements: Basic Bash knowledge, Basic R knowledge

Day Lecture Short Description Exercise Data (needed for Exercises) Materials
8 Transcr lecture Transcriptome assembly using Trinity Transcr exercises RNAseq data
9 DE lecture Differential expression analyses using DESeq2 DE exercises DE data

Part 4: Proteomics and Orthology (4-6.12)

Responsible: Elias DohmenEvelien Jongepier, Carsten Kemena

Requirements: Basic Linux knowledge, Basic R knowledge for the enrichment analysis

Day Lecture Short Description Exercise Data (needed for Exercises) Materials
10 Orthology Orthology clustering in the context of genomes and proteomes. Exercise Orthology
11 Protein Domains Proteomics with Protein Domains as Markers for Protein Orthology. Exercise Domains results_Danio_rerio.pfam
12 Enrichment lecture GO-term analysis and visualization Enrichment exercises

Part 5: Bring your own data (7-8.12)

This section is dedicated to helping you with problems you have with your own data. You can bring your own data and we will help you with questions concerning the topics we covered in this course.