Essential resources for getting started with analysis of single cell data sets

singlecell.md

Created by Natasha Picciani and Jasmine Mah

Getting Started with Single Cell Analysis

Plan for Tuesday (08/24):

Goals

Our goal on Tuesday is to go over the introductory tutorial for single cell RNA-seq analysis using an R package called Seurat and understand the point of each step.

What you need to install

1. Install R (version 4 or higher), RStudio and the latest version of Seurat (v. 4.0.3). See https://satijalab.org/seurat/articles/install.html
2. Dowload the raw data set (https://cf.10xgenomics.com/samples/cell/pbmc3k/pbmc3k_filtered_gene_bc_matrices.tar.gz)

What you need to read

• Current best practices in single-cell RNA-seq analysis: a tutorial (2019): https://doi.org/10.15252/msb.20188746

The tutorial

You can find the tutorial on the following link:

• Basic Introductory Tutorial: https://satijalab.org/seurat/articles/pbmc3k_tutorial.html

Even though the Seurat tutorial provides a brief overview of each step, the current best practices article will give you more in-depth explanations.

Optional readings

• Eleven grand challenges in single cell data science (2020): https://doi.org/10.1186/s13059-020-1926-6

• Current challenges and advances in using single cell RNA-seq in plants (2021): https://doi.org/10.1016/j.molp.2020.10.012

Other Tutorials (not for Tuesday):

• Multi-modal Analysis: https://satijalab.org/seurat/articles/multimodal_vignette.html

Integrated analysis of multimodal single cell data (2021; Seurat Team): https://doi.org/10.1016/j.cell.2021.04.048

Comprehensive integration of single cell data (2019; Seurat Team): https://doi.org/10.1016/j.cell.2019.05.031

• Orchestrating Single Cell Analysis with Bioconductor (this tutorial includes analysis of example datasets from Chapter 25 to Chapter 42):https://bioconductor.org/books/release/OSCA/

Recent development:

• Neuronal diversity and convergence in a visual system developmental atlas (2021): https://doi.org/10.1038/s41586-020-2879-3

• Molecular logic of cellular diversification in the mouse cerebral cortex (2021): https://doi.org/10.1038/s41586-021-03670-5

• Embryo-scale, single-cell spatial transcriptomics (2021): https://doi.org/10.1126/science.abb9536

• Integrating single-cell and spatial transcriptomics to elucidate intercellular tissue dynamics (2021): https://doi.org/10.1038/s41576-021-00370-8

• The single-cell transcriptional landscape of mammalian organogenesis (2019; this study scaled up scRNA-seq to profile 2 million cells): https://doi.org/10.1038/s41586-019-0969-x