Image credit: Lior Pachter

Lecture slides

Homework: DataCamp Intro to R course (~2hrs) - due before the start of class on Feb 13th.


In this class we’ll finally get down to the business of using Kallisto, software for memory-efficient mapping of your raw reads to a reference transcriptome. You’ll carry out this mapping in class, right on your laptop, while we discuss what’s happening ‘under the hood’ with Kallisto and how this compares to more traditional alignment methods. You’ll be introduced to using command line software and will learn about automation and reproducibility through shell scripts.


  • Start a project directory that we’ll use for the rest of the course, and discuss project management and organization
  • Download a reference transcriptome file (talk a bit about what is and is not in a reference file)
  • Build an index from this reference file so that read mapping can be carried out more efficiently
  • Map our raw reads to the index, and talk a bit about what’s happening under the hood


papers and blogs posts on Kallisto

2016 Nature Biotech paper from Lior Pachter’s lab describing Kallisto

2017 Nature Methods paper from Lior Pachter’s lab describing Sleuth

Lior Pachter’s blog post on Kallisto

blog post on pseudoalignments - helps understand how Kallisto maps reads to transcripts

Did you notice that Kallisto is using ‘Expectation Maximization (EM)’ during the alignment? You can read more about what this is here

Kallisto discussions/questions and Kallisto announcements are available on Google groups

General info about ultra lightweight methods for transcript quantification

2014 Nature Biotech paper - describes Sailfish, which implimented the first lightweight method for quantifying transcript expression.

Not quite alignments - Rob Patro, the first author of the Sailfish paper, wrote a nice blog post comparing and contrasting alignment-free methods used by Sailfish, Salmon and Kallisto.

2018 Nature Methods paper describing Salmon - A lightweight aligment tool from Rob Patro and Carl Kinsford. Check out the website too.

2011 Nature Biotechnology - Great primer to better understand what de Bruijn graph is.

Greg Grant’s recent paper comparing different aligners. This should be a helpful guide in choosing alignment software outside of what we used in class.


Harold Pimentel’s talk on alignment (20 min)

Lior Pachter’s talk at CSHL (45 min)