Introduction to R in Biology Course 2017

Improve your data science skills by learning to work with R.

In a nutshell

  • Learn the fundamentals of the R language
  • Understand available data types and functions
  • Extend the functionality of R with packages
  • Use visualization and statistics to analyze your biological data

When?
9 - 11 October 2017

Where?
Leipzig, Germany

This introductory workshop provides a basic training in R for data analysis with a focus on biological applications. Participants will learn how to work with R using the graphical user interface (GUI) RStudio. Available methods for importing, inspecting and computing scientific data are covered. In particular, it will be shown how big data can be explored with pretty graphical visualizations and how these can be exported. At the end of the course, the participants will perform a case study and statistically analyse a real-life gene expression dataset.

Check our course layout.

Get trained by experts

Our trainers have a proven record of academic and/or industrial experience in NGS data analysis. Because up-to-date expert knowledge is needed to answer your questions and know what is important in the field.

Open source NGS tools

We only use open source tools that are free to use. We try to showcase and compare different tools (e.g. NGS mappers), since not every software fits with every task/question.

Learn effectively with well-curated materials

For a optimal learning experience we carefully prepare our learning materials and example data. All materials, tools and results created during the course are for take home with you.

This workshop has been adapted to the needs of beginners and comprises this three course modules:

  1. Introduction to R:
    This module will introduce the essential skills to interact and use R using the R-GUI. Basic datatypes and operations will be shown and first small functions will be written. The installation and usage of R-packages will be shown.
  2. Data handling in R:
    You will learn how to load and handle biological data using R data types, how to run descriptive statistics and create first graphics. Basic probability distributions and statistical tests will be used.
  3. Advanced statistics and data visualization:
    On the last day you will learn how compute linear regressions and how to visualize large datasets. Finally, in a case study you will do your first statistical analysis of a gene expression dataset.

Detailed Course Program


Introduction to R

  • Introduction to R, R-GUI and R-Studio
  • Simple interactions with R
  • Available data types and operations
  • Writing your own functions in R
  • Using R-packages

Data handling in R

  • Data input and data output
  • More complex data types and functions to handle them
  • Descriptive statistics and graphics
  • Basic probability distributions and statistical tests

Advanced statistics and data visualization

  • Linear regression
  • Advanced graphics for large datasets
  • Case study: Statistical analysis of a gene expression dataset

Speakers

Dr. Markus Kreuz (University of Leipzig)
Markus is a computer scientist who specialiced in the analysis of high complex medical data. He works at the Institute for Medical Informatics, Statistics and Epidemiology (IMISE), which belongs to the Medical Faculty of the University of Leipzig. With more than 10 years of experience in analyzing complex data from various medical studies, he is an expert in the analysis of big data in R.

Dr. Mario Fasold (Seamless NGS)
Mario works in the analysis of microarray data since 2007 and developed several bioinformatics tools in R such as the Bioconductor package AffyRNADegradation and the Larpack program package. Since 2011 he specialized in the field of NGS data analysis and helped analysing sequecing data of several large consortium projects.

Dr. Christian Otto (Seamless NGS)
Christian has more than 10 years of experience in the usage of R to answer complex biological questions.

Requirements

  • basic understanding of molecular biology (DNA, RNA, gene expression, PCR, ...)

The target audience is biologists or data analysts with no or little experience in R.

  •   Course materials
  •   Catering during the workshop
  •   Conference dinner
  •   High-performance workstations (no laptop needed)

Attendence

Location: iad Pc-Pool, Rosa-Luxemburg-Stra├če 23, Leipzig, Germany
Language: English
Available seats: 24 (first-come, first-served)

Registration Fee: 680 EUR (excluding VAT)

Travel expenses and accommodation are not covered by the registration fee.

Travel Information - Leipzig

Key dates

Opening Date of Registration: 1 February 2017
Closing Date of Registration: 1 September 2017
Workshop: 9 - 11 October 2017 (8 am - 5 pm)

When you register for this workshop you are agreeing with our Workshop Terms and Conditions. Please read them before you register.


Any Questions? Please feel free to contact our events team.

ecSeq GmbH
Brandvorwerkstr. 43
04275 Leipzig
Germany
Email: events@ecSeq.com