Lecture 8: Basics of Single Cell RNA-seq Data Analysis (07/22/2024)

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What you need to prepare

Install the following packages to prepare your R environment:

  • Seurat
  • Presto (to speed up Seurat)
install.packages("Seurat")
install.packages("devtools") # to be able to install github repository: Presto
devtools::install_github("immunogenomics/presto")

library(Seurat) 
library(presto)

What we will learn

Introduction to scRNA-seq

  • scRNA-seq profiles features of individual cells which help advance science discovery and sequencing and most today’s experiments are done using 10x Genomics

  • scRNA-seq data analysis has several challenges including complexity and noise in the data

  • Seurat and other R/Python package are specially designed for QC and analysis of scRNA-seq data

scRNA-seq data analysis workflow using Seurat package

  • It is important to understand the meaning of each analysis step (theoretical basis can be complicated) and to choose appropriate parameters

  • Biological knowledge/intuition are important in evaluating results

What we will Practice

Basic Analysis Steps in Seurat using pbmc dataset