> For the complete documentation index, see [llms.txt](https://laboratory-of-lipid-metabolism-a.gitbook.io/omics-data-visualization-in-r-and-python/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://laboratory-of-lipid-metabolism-a.gitbook.io/omics-data-visualization-in-r-and-python/introduction/data-set-from-isc-prague-2026.md).

# Data set from ISC Prague 2026

Here we share materials from the R course organized within The International Symposium on Chromatography (ISC) in Prague on 6.09.2026.

### 1. tidyverse for data preparation and analysis (12:30– 14:00)

* Installation of R and RStudio. Quick orientation.
* Packages (libraries) and their installation.
* Fundamental data structures. 
* Loading data into R. Preferred data format.
* Preprocessing data types in R.
* Useful R tricks for data preparation and mining.
* Missing values handling.
* Data transformation.
* Computation of summary statistics.

### 2. data analysis and visualization (14:30– 15:45)

1. Creating box plots in R with:

* ggstatsplot,
* tidyplots,
* and tidyverse (ggplots).

2\. Creating chromatogram in R (example added).

3\. Univariate statistics in R with rstatix: 

* *t*-test (with volcano plot added).
* ANOVA,
* Post-hoc testing (with box plot annotations added).

4\. Multivariate analysis – principal component analysis (PCA) in R with: 

* FactoMineR / factoextra,
* mixOmics.

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