Kallisto

Inroduction

It's the new (2015) way of evaluating gene expression abundance from NGS short reads.

It is considerably faster than other methods (like those based on say, RSEM) in that it omits the conventional alignment step, and instead calculates what it calls compatibility classes for each read, which are transcripts that the read could align with, if a proper alignment had taken place.

Steps in Brief

First off, we need an assembly of some sort: a reference transcriptome or genome, which may have been de-novo assembled. As is often the case, this needs to be indexed first. Kallisto has its own tool for that. Here we use the example data from the Edgen RNAseq pipeline:

kallisto index -i mm10_chr19-1-20000000.idx mm10_chr19-1-20000000.fasta 

Explanation:

• -i is not the input option but rather the index name option, which is the command is the chosen output name for the index file.
• the reference or assembly follows with no associated option

Armed with the index file, kallisto is now ready to quantify. Here is the format of the command:

kallisto quant -i <index_file> -o outputdir <then_follow_read_pair_file>

Sleuth

Sleuth is an associated program for Kallisto, when dealing with several samples for which we have pair-end read sets. It is implemented in R and is available in Bioconductor.

It's installed with

source("http://bioconductor.org/biocLite.R")
biocLite("devtools")    # only if devtools not yet installed
biocLite("pachterlab/sleuth")

Sleuth is made up of the following programs:

• sleuth_prep, preparation stage.
• sleuth_fit, to fit a model
• sleuth_wt, for hypothesis testing
• sleuth_lrt, also for hypothesis testing

Links

• Kallisto's own getting started page at starting
• sleuth manual
• Getting started with Sleuth
• benchtobioinformatics
• Andrew MacKenzie

Analysis

Also part of Lior Pachter's lab is the Sleuth software and this is recommended for analysis of kallisto output