Last updated: 2021-06-30

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Rmd a63decb Davis McCarthy 2021-06-29 Minor tweaks
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Introduction

In this workshop, we will introduce the data infrastructure for scRNA-seq analysis in R and practice a workflow of scRNAseq analysis; from pre-processing, quality control to dimensionality reduction and clustering. We will then demonstrate the usage of marker genes for cell type annotation and an automatic approach for matching query cells to a reference atlas with labels.

  1. single-cell RNAseq analysis workflow for cell type identification

devtools::session_info()
─ Session info ───────────────────────────────────────────────────────────────
 setting  value                       
 version  R version 4.0.3 (2020-10-10)
 os       macOS Big Sur 10.16         
 system   x86_64, darwin17.0          
 ui       X11                         
 language (EN)                        
 collate  en_AU.UTF-8                 
 ctype    en_AU.UTF-8                 
 tz       Australia/Melbourne         
 date     2021-06-30                  

─ Packages ───────────────────────────────────────────────────────────────────
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[1] /Users/dmccarthy/Library/R/4.0/library
[2] /Library/Frameworks/R.framework/Versions/4.0/Resources/library