2022-03-25

de.NBI / ELIXIR-DE will offer a training course at Proteomic Forum / EuPA 2022. Here are the details: 

Educators:
Nils Hoffmann (FZ Jülich / ELIXIR-DE / de.NBI)

Date:
Sunday, April 3rd 2022

Location:
On-Site, Leipzig, as part of the educational day of Proteomic Forum / EuPA 2022

Registration:
During conference registration, please register for the “Educational Day” (Session 1)

Contents:
This course will provide participants with the necessary knowledge to conduct a differential analysis of high-throughput quantitative proteomics data using R. As we start with a basic introduction to the popular statistical programming language, no prior knowledge on R is required.
The basic statistical background on utilized methods is explained in order to enable the participants to assess their own as well as published workflows critically. In this regard the course will touch upon
- statistical inference: hypotheses, type I and II error
- location tests (t-test)
- multiple testing

This course introduce participants to the ggplot2 package in R to create informative and beautiful figures to communicate your omics data and analysis results.
We will cover the following topics:
- Usage of the tidyverse for data preprocessing
- Usage of the ggplot2 R package
- Presentation of different types of graphics and when to use them
- Customization of graphics

Learning goals:
- Independent usage of basic R functions including data import and export, basic plots and statistical tests
- Basic understanding of statistical methods applied in differential analyses
- Basics of using the ggplot2 R package to create and customize graphics for omics data

Prerequisites:
- Basic understanding of high-dimensional data sets from quantitative proteomics or other life sciences
- No prior knowledge on R required, basic knowledge of R (e.g. data import, basic plots) beneficial
- Laptop (Wifi will be available on-site) with R and preferrably RStudio installed to follow along

Keywords:
R; tidyverse; ggplot2; high-throughput data; omics; proteomics; data analysis, graphics, data preprocessing

Tools:
Download and more information on R here:
 https://cran.r-project.org/
We recommend using an editor such as RStudio, see
 www.rstudio.com

Contact:
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