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DTSTAMP:20260407T225956Z
UID:40cd269a-25eb-4e95-a974-5b65b9a77c1c
DTSTART:20200727T210000Z
DTEND:20200727T215500Z
DESCRIPTION:This workshop will present how to perform analysis of RNA seque
 ncing data following the tidy data paradigm. The tidy data paradigm provid
 es a standard way to organise data values within a dataset\, where each va
 riable is a column\, each observation is a row\, and data is manipulated u
 sing an easy-to-understand vocabulary. Most importantly\, the data structu
 re remains consistent across manipulation and analysis functions. \n\nThis
  can be achieved for RNA sequencing data with the [tidybulk](github.com/st
 emangiola/tidybulk)\, [tidyHeatmap](github.com/stemangiola/tidyHeatmap) an
 d tidyverse packages. The package [tidybulk](github.com/stemangiola/tidybu
 lk) provides a tidy data structure and a modular framework for bulk transc
 riptional analyses. tidyHeatmap provides a tidy implementation of ComplexH
 eatmap. These packages are part of the tidytranscriptomics suite that intr
 oduces a tidy approach to RNA sequencing data.\n\nThe topics presented in 
 this workshop will be\n\n- Data exploration\n- Data dimensionality reducti
 on and clustering\n- Differential gene expression analysis \n- Data visual
 isation\n\n## Pre-requisites\n\n* Basic knowledge of RStudio\n* Familiarit
 y with tidyverse syntax\n\nRecommended Background Reading \n[Introduction 
 to R for Biologists](https://melbournebioinformatics.github.io/r-intro-bio
 logists/intro_r_biologists.html)
SUMMARY:A Tidy Transcriptomics introduction to RNA-Seq analyses
URL;VALUE=URI:http://bioc2020.bioconductor.org/schedule-day-one
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