Last updated: 2021-07-07
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Knit directory: svi-sahmri_scrna-seq-workshop_2021-july/
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| html | ed221af | Davis McCarthy | 2021-06-29 | Tweaks to workflowr pages |
| Rmd | 8cdfd4d | Davis McCarthy | 2021-06-29 | Updating materials for workshop in July 2021 |
| html | 8cdfd4d | Davis McCarthy | 2021-06-29 | Updating materials for workshop in July 2021 |
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, marker gene detection and cell type annotation - with plenty more along the way!
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).
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…
Follow this link for the single-cell RNA-seq analysis workflow focusing on cell type identification.
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date 2021-07-07
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