RT Journal Article
SR Electronic
T1 chewBBACA: A complete suite for gene-by-gene schema creation and strain identification
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 173146
DO 10.1101/173146
A1 Mickael Silva
A1 Miguel Machado
A1 Diogo N. Silva
A1 Mirko Rossi
A1 Jacob Moran-Gilad
A1 Sergio Santos
A1 Mario Ramirez
A1 João André Carriço
YR 2017
UL http://biorxiv.org/content/early/2017/10/23/173146.abstract
AB Gene-by-gene approaches are becoming increasingly popular in bacterial genomic epidemiology and outbreak detection. However, there is a lack of open-source scalable software for schema definition and allele calling for these methodologies. The chewBBACA suite was designed to assist users in the creation and evaluation of novel whole-genome or core-genome gene-by-gene typing schemas and subsequent allele calling in bacterial strains of interest. The software can run in a laptop or in high performance clusters making it useful for both small laboratories and large reference centers. ChewBBACA is available at https://github.com/B-UMMI/chewBBACA or as a docker image at https://hub.docker.com/r/ummidock/chewbbaca/.DATA SUMMARYAssembled genomes used for the tutorial were downloaded from NCBI in August 2016 by selecting those submitted as Streptococcus agalactiae taxon or sub-taxa. All the assemblies have been deposited as a zip file in FigShare (https://figshare.com/s/9cbe1d422805db54cd52), where a file with the original ftp link for each NCBI directory is also available.Code for the chewBBACA suite is available at https://github.com/B-UMMI/chewBBACA while the tutorial example is found at https://github.com/B-UMMI/chewBBACA_tutorial.DATA SUMMARYI/We confirm all supporting data, code and protocols have been provided within the article or through supplementary data files. ⊠IMPACT STATEMENT The chewBBACA software offers a computational solution for the creation, evaluation and use of whole genome (wg) and core genome (cg) multilocus sequence typing (MLST) schemas. It allows researchers to develop wg/cgMLST schemes for any bacterial species from a set of genomes of interest. The alleles identified by chewBBACA correspond to potential coding sequences, possibly offering insights into the correspondence between the genetic variability identified and phenotypic variability. The software performs allele calling in a matter of seconds to minutes per strain in a laptop but is easily scalable for the analysis of large datasets of hundreds of thousands of strains using multiprocessing options. The chewBBACA software thus provides an efficient and freely available open source solution for gene-by-gene methods. Moreover, the ability to perform these tasks locally is desirable when the submission of raw data to a central repository or web services is hindered by data protection policies or ethical or legal concerns.