No lecture slides for this class. We’ll spend the entire time working on Step 1 script.


We’ll begin this class by reviewing how to access R packages and help documentation, as well as understanding the basic structure of an R script and RStudio project. We’ll then access annotation data before reading our Kallisto results into R.

Learning objectives

  • Review basic elements of an R script
  • Learn how to access R packages, and their help documentation
  • Understand the importance of a study design file
  • Access annotation information for transcripts using Bioconductor
  • Read Kallisto transcript abundance measurements into the R environment using TxImport


Step 1 script

Lecture video

“Warning - videos below are from 2020 lectures and will soon be updated for 2021.”

Part 1 - Starting Step 1 script

Part 2 - Tapping into annotation databases and reading Kallisto data into R


Differential analysis of RNA-seq incorporating quantification uncertainty. Nature Methods, June, 2017 - Original paper describing Sleuth

Lior Pachter’s lab post on Sleuth

vignette for the Tximport package - the R package we’ll use to read the Kallisto mapping results into R.

Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences* F1000Research, Dec 2015. This paper describes the Tximport package and its application for handling transcript-level expression measurments from lightweight aligners (Salmon, Sailfish, Kallisto)