> 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/performing-fundamental-operations-on-omics-data-using-r/useful-r-tricks-and-features-in-omics-mining.md).

# Useful R tricks and features in OMICs mining

Here is one of the first facts that you need to know - your data usually are not in the form that enables immediate use in R for computations or preparing visualization. However, using a couple of simple transformations, which form a pre-processing pipeline, you can get your data ready for subsequent mining. 

This chapter includes a set of essential R pre-processing operations, which is good to know before performing OMICs analysis. Such useful tricks, features, and functions are offered by collections like tidyverse or tidymodels. Let's dive in.