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As can be seen in the workflow below, there are several workflow options. The one we’ll be using is the complete Cell Ranger workflow, using the tools cellranger mkgtf and cellranger mkref for reference genome preparation and cellranger count for both aligning sequences to the reference genome and quantifying expression per gene per cell, for each sample.

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1b. Creating a samplesheet

1c. Running scrnaseq as a PBS script

2. Seurat

Seurat is:

A toolkit for quality control, analysis, and exploration of single cell RNA sequencing data. 'Seurat' aims to enable users to identify and interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse types of single cell data.

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  1. Open RStudio (you can type it in the Windows search bar)

  2. Create a new R script: ‘File’ → “New File” → “R script”

  3. Save this script where your samples folders are (‘File’ → ‘Save’). These should be on your H or W drive. Save the script file as scrnaseq.R

In the following sections you will be copying and running the R code into your scrnaseq.R script.

Cell Ranger (and nfcore/scrnaseq) generates a default folder and file output structure. There will be a main folder that contains all the sample subfolders (NOTE: this is where you must save your R script). Each sample folder will have an ‘outs’ subfolder. This ‘outs’ folder contains a ‘filtered_feature_bc_matrix’ folder, which contains the files that Seurat uses in its analysis.

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You can manually set your working directory in RStudio by selecting ‘Session' -> 'Set working directory' -> 'Choose directory'. Choose the same directory as you saved your scrnaseq.R script, previous section. This will output the setwd(...) command with your working directory into the console window (bottom left panel). Copy this command to replace the default setwd(...) line in your R script.

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