Advanced


In this course you will learn about using R for the analysis of proteomics data. We will focus on data preprocessing methods and advanced methods for data analysis. In this regard the course will touch upon:
    • data normalization
    • quality control, handling of missing values
    • clustering, heatmaps
    • ROC-curves

Learning goals:
    • Independent usage of R functions for
        - Data preprocessing
        - Plots and graphs
        - Statistical methods for data analysis
        - Use of additional R packages
    • Deeper understanding of statistical methods applied in differential analyses

Prerequisites:
    • Basic understanding of high-dimensional data sets from quantitative proteomics or other life sciences;
    • Basic knowledge of R (e.g. data import, basic plots, t-test, for loop) and basic knowledge of differential analysis of proteomics data. Both can for example be gained from our e-Learning course “Differential analysis of quantitative proteomics data”.

Download Training material here:
https://www.denbi.de/images/Training/eLearning/Material_Advanced_Rcourse.zip

Download and more information on R here:
https://cran.r-project.org/

We recommend using an editor such as RStudio, see
https://www.rstudio.com