kallisto is a program for quantifying abundances of transcripts from RNA-Seq data, or more generally of target sequences using high-throughput sequencing reads. It is based on the novel idea of pseudoalignment for rapidly determining the compatibility of reads with targets, without the need for alignment.

References:

• NL Bray, H Pimentel, P Melsted and L Pachter, Near optimal probabilistic RNA-seq quantification, Nature Biotechnology 34, p 525--527 (2016). doi:10.1038/nbt.3519

• Kallisto Main Site
• Google Group

• Module Name: kallisto (see the modules page for more information)
• Example files in $KALLISTO_HOME/test
• BAM files (--genomebam) have not been supported since version 0.48.0. See the release notes for other deprecations/removals.

Allocate an interactive session and run the program.
Sample session (user input in bold):

[user@biowulf]$ sinteractive
salloc.exe: Pending job allocation 46116226
salloc.exe: job 46116226 queued and waiting for resources
salloc.exe: job 46116226 has been allocated resources
salloc.exe: Granted job allocation 46116226
salloc.exe: Waiting for resource configuration
salloc.exe: Nodes cn3144 are ready for job

[user@cn3144 ~]$ cp -r $KALLISTO_HOME/test/* . 
[user@cn3144 ~]$ kallisto index -i transcripts.kidx transcripts.fasta.gz

[build] loading fasta file transcripts.fasta.gz
[build] k-mer length: 31
[build] counting k-mers ... done.
[build] building target de Bruijn graph ...  done 
[build] creating equivalence classes ...  done
[build] target de Bruijn graph has 27 contigs and contains 22118 k-mers 

[user@cn3144 ~]$ kallisto quant \
 -i transcripts.kidx \
 -b 30 \
 -o kallisto_out \
 --gtf transcripts.gtf.gz \
 --chromosomes chrom.txt \
 reads_1.fastq.gz reads_2.fastq.gz

[quant] fragment length distribution will be estimated from the data
[index] k-mer length: 31
[index] number of targets: 14
[index] number of k-mers: 22,118
[index] number of equivalence classes: 20
Warning: 13 transcripts were defined in GTF file, but not in the index
[quant] running in paired-end mode
[quant] will process pair 1: reads_1.fastq.gz
                             reads_2.fastq.gz
[quant] finding pseudoalignments for the reads ... done
[quant] processed 10,000 reads, 9,413 reads pseudoaligned
[quant] estimated average fragment length: 178.02
[   em] quantifying the abundances ... done
[   em] the Expectation-Maximization algorithm ran for 52 rounds
[bstrp] running EM for the bootstrap: 30

[user@cn3144 ~]$ exit
salloc.exe: Relinquishing job allocation 46116226
[user@biowulf ~]$

Create a batch input file (e.g. kallisto.sh). For example:

#!/bin/sh
set -e
module load kallisto

kallisto index -i transcripts.kidx transcripts.fasta.gz

kallisto quant \
 -i transcripts.kidx \
 -b 30 \
 -o kallisto_out \
 --gtf transcripts.gtf.gz \
 --chromosomes chrom.txt \
 reads_1.fastq.gz reads_2.fastq.gz

Submit this job using the Slurm sbatch command.

sbatch [--cpus-per-task=#] [--mem=#] kallisto.sh

Create a swarmfile (e.g. kallisto.swarm). For example:

kallisto quant -i transcripts.kidx -b 30 -o kallisto/sample-01 --gtf transcripts.gtf.gz --chromosomes chrom.txt sample01/reads_{1,2}.fastq.gz
kallisto quant -i transcripts.kidx -b 30 -o kallisto/sample-02 --gtf transcripts.gtf.gz --chromosomes chrom.txt sample02/reads_{1,2}.fastq.gz
kallisto quant -i transcripts.kidx -b 30 -o kallisto/sample-03 --gtf transcripts.gtf.gz --chromosomes chrom.txt sample03/reads_{1,2}.fastq.gz
kallisto quant -i transcripts.kidx -b 30 -o kallisto/sample-04 --gtf transcripts.gtf.gz --chromosomes chrom.txt sample04/reads_{1,2}.fastq.gz

Submit this job using the swarm command.

swarm -f kallisto.swarm [-g #] [-t #] --module kallisto