Corticall: A graph-based de novo mutation caller based on traversing (Mc)Cortex de novo assembly graph and link data.
git clone https://github.com/mcveanlab/Corticall
cd Corticall
ant
java -jar dist/corticall.jar -h
Corticall is a Java-based de novo mutation (DNM) caller based on linked multi-color de Bruijn graphs (LdBG) produced by McCortex. It is able to leverage multiple reference sequences to better characterize DNMs in otherwise inaccessible regions of canonical reference genomes.
Corticall may also be used as a class library for performing efficient, low-memory traversals on LdBGs. The most important functionalities provided are:
- iterating over records in a Cortex graphs
- random access (by binary search) to Cortex graph records
- performing simple walks (i.e. extracting a contig, optionally using links to disambiguate junction choices)
- performing walks assisted by one or more reference sequences in a manner consistent with link information
- performing depth-first searches with custom stopping rules (useful for finding interesting graph motifs)
- aligning k-mers and contigs back to reference sequences
Corticall handles the heavy lifting when operating with these data structures, permitting developers to concentrate on the genome analysis and variant calling tools that can be written on top of this API.
Corticall is released under the Apache 2.0 license. The latest code is freely available at Github.
Corticall has the following dependencies:
- Java8: needed for runtime and development kit
- Apache Ant: for dependency fetching and compilation
Additional recommended software:
- McCortex: for building Cortex graphs and link annotations
To download and compile:
git clone https://github.com/mcveanlab/Corticall
cd Corticall
ant
To run (and get a listing of available commands):
java -jar dist/corticall.jar
To get help for a specific command (e.g. "Call"):
java -jar dist/corticall.jar Call
Please contact Kiran V Garimella (kiran@broadinstitute.org) with any questions/comments/concerns/cake. Feedback, bug reports, and pull requests are welcome.
For a pythonic take on programmatically accessing McCortex linked multi-color de Bruijn graphs, see Winni Kretzschmar's cortexpy project.
The original multi-color de Bruijn graph paper can be found at:
- "De novo assembly and genotyping of variants using colored de Bruijn graphs", Iqbal, Caccamo, Turner, Flicek, McVean (Nature Genetics) (2012) (doi:10.1038/ng.1028) http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3272472
Our manuscript on linked multi-color de Bruijn graphs is now available via Bioinformatics at:
- "Integrating long-range connectivity information into de Bruijn graphs", Turner, Garimella, Iqbal, McVean (Bioinformatics) (2018) (doi:10.1093/bioinformatics/bty157) https://www.ncbi.nlm.nih.gov/pubmed/29554215
A manuscript preprint for Corticall, our de novo assembly approach to de novo mutation detection in pathogens, can be found at:
- "Detection of simple and complex de novo mutations without, with, or with multiple reference sequences", Garimella, Iqbal, Krause, Campino, Kekre, Drury, Kwiatkowski, Sa, Wellems, McVean (2019) (doi:10.1101/698910) https://www.biorxiv.org/content/10.1101/698910v1