Supporting data for ‘Piggy: A Rapid, Large-Scale Pan-Genome Analysis Tool for Intergenic Regions in Bacteria’

Dataset type: Software, Genomic
Data released on February 22, 2018

Thorpe HA; Bayliss SC; Sheppard SK; Feil EJ (2018): Supporting data for ‘Piggy: A Rapid, Large-Scale Pan-Genome Analysis Tool for Intergenic Regions in Bacteria’ GigaScience Database. http://dx.doi.org/10.5524/100410

DOI10.5524/100410

Despite overwhelming evidence that variation in intergenic regions (IGRs) in bacteria can directly influence phenotypes, most current approaches for analysing pan-genomes focus exclusively on protein-coding sequences. To address this we present Piggy, a novel pipeline that emulates Roary except that it is based only on IGRs. We demonstrate the use of Piggy for pan-genome analyses of Staphylococcus aureus and Escherichia coli using large genome datasets. For S. aureus, we show that highly divergent (“switched”) IGRs are associated with differences in gene expression, and we establish a multi-locus reference database of IGR alleles (igMLST; implemented in BIGSdb). Piggy is available at https://github.com/harry-thorpe/piggy and registered with SciCrunch (RRID: SCR_015941).

Additional details

Read the peer-reviewed publication(s):

Thorpe, H. A., Bayliss, S. C., Sheppard, S. K., & Feil, E. J. (2018). Piggy: a rapid, large-scale pan-genome analysis tool for intergenic regions in bacteria. GigaScience, 7(4). doi:10.1093/gigascience/giy015

Additional information:

https://github.com/harry-thorpe/piggy

Accessions (data not in GigaDB):

BioProject: PRJEB2756
BioProject: PRJEB8221
GENBANK: HE681097
GENBANK: MRSA252
GENBANK: BX571856
GENBANK: AP009351
GENBANK: AM990992
http://datadryad.org/resource/doi:10.5061/dryad.d7d71





File NameSample IDData TypeFile FormatSizeRelease Date 
GitHub archivearchive3.78 MB2018-02-01
ReadmeTEXT1.41 KB2018-02-01
Displaying 1-2 of 2 File(s).
Funding body Awardee Award ID Comments
Medical Research Council S Peacock G1000803 United Kingdom Clinical Research Collaboration Translational Infection Research Initiative
Date Action
February 22, 2018 Dataset publish
July 3, 2018 Manuscript Link added : 10.1093/gigascience/giy015