Spatial transcriptomics Nanocourse

Audience Computational skills required Duration
Biologists Introduction to R 1 session in-person (~1h 45 min of trainer-led time)

Description

This repository contains materials for a module which is part of a Nanocourse organized by the Single Cell Core at HMS. The nanocourse titled “Spatial Transcriptomics: Key Technologies, Experimental Considerations, and Data Analysis” introduces the fundamentals of data analysis for spatial transcriptomics, including common techniques and tools. In this module we walk through the analysis workflow for Visium HD data analysis.

Learning Objectives

Dataset

The dataset which is used in the pre-reading activities can be found at the link below.

Lessons

Workshop schedule (trainer-led learning)

Installation Requirements

Applications

Download the most recent versions of R and RStudio for your laptop:

Packages for R

Note 1: Install the packages in the order listed below.

Note 2:  All the package names listed below are case sensitive!

Note 3: If you have a Mac with an M1 chip, download and install this tool before intalling your packages: https://mac.r-project.org/tools/gfortran-12.2-universal.pkg

Note 4: At any point (especially if you’ve used R/Bioconductor in the past), in the console R may ask you if you want to update any old packages by asking Update all/some/none? [a/s/n]:. If you see this, type “a” at the prompt and hit Enter to update any old packages. Updating packages can sometimes take quite a bit of time to run, so please account for that before you start with these installations.

Note 5: If you see a message in your console along the lines of “binary version available but the source version is later”, followed by a question, “Do you want to install from sources the package which needs compilation? y/n”, type n for no, and hit enter.

(1) Install the packages listed below from CRAN using the install.packages() function.

  1. SFEData
  2. scuttle
  3. scater
  4. scran
  5. bluster
  6. BiocParallel
  7. Voyager
  8. fastverse
  9. ggplot2
  10. pals
  11. tidyverse
  12. Seurat
  13. patchwork
  14. qs
  15. quadprog
  16. remotes
  17. devtools
  18. BiocManager

Please install them one-by-one as follows:

install.packages("tidyverse")
install.packages("Seurat")
install.packages("patchwork")
& so on ...

(2) Install the packages listed below from Bioconductor using the BiocManager::install() function.

  1. glmGamPoi

Please install glmGamPoi as follows:

library(BiocManager)
BiocManager::install("glmGamPoi")
BiocManager::install("pachterlab/SpatialFeatureExperiment", ref = "devel")

(3) Install the packages listed below from GitHub using the given remotes:install_github or devtools::install_github command.

  1. SeuratWrappers : remotes::install_github('satijalab/seurat-wrappers')
  2. Banksy : remotes::install_github("prabhakarlab/Banksy@devel")
  3. spacexr : devtools::install_github("dmcable/spacexr", build_vignettes = FALSE)

(4) Finally, please check that all the packages were installed successfully by loading them one at a time using the library() function.

library(SpatialFeatureExperiment)
library(SFEData)
library(scuttle)
library(scater)
library(scran)
library(bluster)
library(BiocParallel)
library(Voyager)
library(fastverse)
library(ggplot2)
library(pals)
library(tidyverse)
library(Seurat)
library(patchwork)
library(qs)
library(quadprog)
library(remotes)
library(devtools)
library(BiocManager)
library(glmGamPoi)
library(SeuratWrappers)
library(Banksy)
library(spacexr)

(5) Once all packages have been loaded, run sessionInfo().

sessionInfo()

These materials have been developed by members of the teaching team at the Harvard Chan Bioinformatics Core (HBC) RRID:SCR_025373. These are open access materials distributed under the terms of the Creative Commons Attribution license (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.