To run the Cannoli interactive shell, based on the ADAM shell, which in turn extends the
Apache Spark shell, use cannoli-shell.
Wildcard import from ADAMContext to add implicit methods to SparkContext for loading
alignments, features, fragments, genotypes, reads, sequences, slices, variant contexts,
or variants, such as sc.loadPairedFastqAsFragments below.
Wildcard import from Cannoli to add implicit methods for calling external commands to the
genomic datasets loaded by ADAM, such as reads.alignWithBwaMem below.
To run Cannoli commands from the command line, use cannoli-submit.
Note the -- argument separator between Spark arguments and Cannoli command arguments.
$ ./bin/cannoli-submit --help
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Usage: cannoli-submit [<spark-args> --] <cannoli-args>
Choose one of the following commands:
CANNOLI
bcftoolsCall : Call variant contexts with bcftools call.
bcftoolsMpileup : Call variants from an alignment dataset with bcftools mpileup.
bcftoolsNorm : Normalize variant contexts with bcftools norm.
bedtoolsIntersect : Intersect the features in a feature dataset with Bedtools intersect.
blastn : Align DNA sequences in a sequence dataset with blastn.
bowtie : Align paired-end reads in a fragment dataset with Bowtie.
bowtie2 : Align paired-end reads in a fragment dataset with Bowtie 2.
singleEndBowtie2 : Align unaligned single-end reads in an alignment dataset with Bowtie 2.
bwaMem : Align paired-end reads in a fragment dataset with bwa mem.
singleEndBwaMem : Align unaligned single-end reads in an alignment dataset with bwa mem.
bwaMem2 : Align paired-end reads in a fragment dataset with Bwa-mem2.
singleEndBwaMem2 : Align unaligned single-end reads in an alignment dataset with Bwa-mem2.
freebayes : Call variants from an alignment dataset with Freebayes.
gem : Align paired-end reads in a fragment dataset with GEM-Mapper.
magicBlast : Align paired-end reads in a fragment dataset with Magic-BLAST.
minimap2 : Align paired-end reads in a fragment dataset with Minimap2.
longMinimap2 : Align long reads in a sequence dataset with Minimap2.
singleEndMinimap2 : Align unaligned single-end reads in an alignment dataset with Minimap2.
samtoolsMpileup : Call variants from an alignment dataset with samtools mpileup.
snap : Align paired-end reads in a fragment dataset with SNAP.
snpEff : Annotate variant contexts with SnpEff.
star : Align paired-end reads in a fragment dataset with STAR-Mapper.
singleEndStar : Align unaligned single-end reads in an alignment dataset with STAR-Mapper.
unimap : Align paired-end reads in a fragment dataset with Unimap.
longUnimap : Align long reads in a sequence dataset with Unimap.
singleEndUnimap : Align unaligned single-end reads in an alignment dataset with Unimap.
vep : Annotate variant contexts with Ensembl VEP.
vtNormalize : Normalize variant contexts with vt normalize.
CANNOLI TOOLS
interleaveFastq : Interleaves two FASTQ files.
sampleReads : Sample reads from interleaved FASTQ format.
External commands wrapped by Cannoli should be installed to each executor node in the cluster
Cannoli
Distributed execution of bioinformatics tools on Apache Spark. Apache 2 licensed.
Hacking Cannoli
Install
To build
Installing Cannoli
Cannoli is available in Conda via Bioconda, https://bioconda.github.io/
Cannoli is available in Homebrew via Brewsci/bio, https://github.com/brewsci/homebrew-bio
Cannoli is available in Docker via BioContainers, https://biocontainers.pro
Find
{tag}on the tag search page, https://quay.io/repository/biocontainers/cannoli?tab=tagsUsing Cannoli interactively from the shell
To run the Cannoli interactive shell, based on the ADAM shell, which in turn extends the Apache Spark shell, use
cannoli-shell.Wildcard import from
ADAMContextto add implicit methods to SparkContext for loading alignments, features, fragments, genotypes, reads, sequences, slices, variant contexts, or variants, such assc.loadPairedFastqAsFragmentsbelow.Wildcard import from
Cannolito add implicit methods for calling external commands to the genomic datasets loaded by ADAM, such asreads.alignWithBwaMembelow.Running Cannoli from the command line
To run Cannoli commands from the command line, use
cannoli-submit.Note the
--argument separator between Spark arguments and Cannoli command arguments.External commands wrapped by Cannoli should be installed to each executor node in the cluster
or can be run using Docker
or can be run using Singularity