Move pre-requisites

Author: mblue9

README.md

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 <img style="height:100px;" alt="tidybulk" src="https://github.com/Bioconductor/BiocStickers/blob/master/tidybulk/tidybulk.png?raw=true"/>
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-### Pre-requisites
-
-* Basic familiarity with single-cell transcriptomic analyses
-* Basic familiarity with tidyverse
-
 ## Workshop Description
 
 This tutorial will present how to perform analysis of single-cell RNA sequencing data following the tidy data paradigm. The tidy data paradigm provides a standard way to organise data values within a dataset, where each variable is a column, each observation is a row, and data is manipulated using an easy-to-understand vocabulary. Most importantly, the data structure remains consistent across manipulation and analysis functions.
 
 This can be achieved with the integration of packages present in the R CRAN and Bioconductor ecosystem, including [tidySingleCellExperiment](https://stemangiola.github.io/tidySingleCellExperiment/) and [tidyverse](https://www.tidyverse.org/). These packages are part of the tidytranscriptomics suite that introduces a tidy approach to RNA sequencing data representation and analysis. For more information see the [tidy transcriptomics blog](https://stemangiola.github.io/tidytranscriptomics/).
 
+### Pre-requisites
+
+* Basic familiarity with single-cell transcriptomic analyses
+* Basic familiarity with tidyverse
+
 ## Workshop goals
 
 * To approach single-cell data representation and analysis though a tidy data paradigm, integrating tidyverse with tidySingleCellExperiment.