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---
title: "SAHMRI Single-cell RNA-seq Analysis Workshop"
site: workflowr::wflow_site
output:
  workflowr::wflow_html:
    toc: true
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

##  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
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control to dimensionality reduction and clustering, marker gene detection and cell type annotation - with plenty more along the way! 


## Setup requirements

We use the Bioconductor single-cell ecosystem for this workshop. Thus, participants will need a recent version of R (version 4.0+) and a set of specific packages that we use.

The code snippet below will install the necessary packages for you in R (i.e. run the following code at the R prompt in an R or RStudio session). The first line installs the `BiocManager` package, which is the preferred package for then installing Bioconductor packages. The next (long) line then installs the necessary Bioconductor packages (and any dependencies).

```{r package-installation, eval=FALSE}
install.packages("BiocManager")
BiocManager::install(c("scRNAseq",
                       "scater",
                       "scran",
                       "clustree",
                       "BiocSingular",
                       "Rtsne",
                       "BiocFileCache",
                       "DropletUtils",
                       "EnsDb.Hsapiens.v86",
                       "schex",
                       "celldex",
                       "SingleR",
                       "gridExtra"))
```

If you have trouble with the package installation, please ask a colleague for help.

Once you have installed the packages, you're ready to go with the workshop. So let's...


## Get crackin'
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Follow this link for the [single-cell RNA-seq analysis workflow focusing on cell type identification](sahmri_analysis-workflow.html).