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
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
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.
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)