Prerequisites
Do these before coming to the workshop:
1.) Command line tutorial
You are expected to be familiar with basic command line usage before the workshop. If you are unfamiliar with the command line, below are some suggested tutorials. If you have a Mac computer you can use the “Terminal” application to complete these tutorials. If you have access to a linux server at your institution you could also do them there. If neither of those is available you can try a free online terminal application that runs in your browser such as sandbox.io (also includes several relevant tutorials). Work through at least some of the below options.
2.) Introduction to R tutorial
Knowing R is critical to this workshop. Using R installed on your computer, please work through at least some of the following tutorials.
- R Tutorial (W3 Schools)
- Introduction to R (datacamp) (Take first free chapter)
- R Review & Assessment
- GenViz Intro R tutorial (Note this tutorial is more advanced, especially the final exerxise, and not required)
3.) Reading materials
Please browse these articles, select a few that fill in knowledge gaps, and review before coming to the workshop:
Some recent reviews (2024-2025)
- Experimental design. Technical considerations for planning an RNA-Sequencing experiment.
- Spatial transcriptomics. Review of spatial transcriptomics data alignment and integration.
- Bioinformatics for transcriptomics. Bioinformatics perspectives on transcriptomics: A comprehensive review of bulk and single-cell RNA sequencing analyses.
- Single-cell + long reads. Advances in single-cell long-read sequencing technologies.
- Deep learning. Deep learning in single-cell and spatial transcriptomics data analysis: advances and challenges from a data science perspective.
Some slightly older but excellent reviews (2019-2023)
- RNA-seq data fundamentals. RNA Sequencing: The Teenage Years.
- RNA-seq analysis and statistics fundamentals. RNA Sequencing Data: Hitchhiker’s Guide to Expression Analysis.
- RNA-seq analysis for tumor immunity. Tutorial: integrative computational analysis of bulk RNA-sequencing data to characterize tumor immunity using RIMA.
- scRNA-seq technologies and applications. Single-cell RNA sequencing technologies and applications: A brief overview.
- DNA sequencing and variant calling overview Novel sequencing technologies and bioinformatic tools for deciphering the non-coding genome.
Optional readings:
The above are just a few published examples that we find particularly good. We have collected a much more extensive list of resources below. Simply take a look at these and note for future reference. Note, these are focused primary towards RNAseq analysis but are often more generally applicable.