From 4b496c75fe8ae714c13ceee115b3c9de161f5a9a Mon Sep 17 00:00:00 2001 From: mblue9 Date: Sat, 23 Jul 2022 11:14:20 +0100 Subject: [PATCH] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 2beaf68..80bcfa3 100755 --- a/README.md +++ b/README.md @@ -11,7 +11,7 @@ ## 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 tutorial will showcase 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/).