PANINI : Pangenome Neighbour Identification for Bacterial Populations

Show simple item record

dc.contributor University of Helsinki, Helsinki Institute for Information Technology en
dc.contributor University of Helsinki, Helsinki Institute for Information Technology en
dc.contributor.author Abudahab, Khalil
dc.contributor.author Prada, Joaquin M.
dc.contributor.author Yang, Zhirong
dc.contributor.author Bentley, Stephen D.
dc.contributor.author Croucher, Nicholas J.
dc.contributor.author Corander, Jukka
dc.contributor.author Aanensen, David M.
dc.date.accessioned 2019-05-28T14:15:02Z
dc.date.available 2019-05-28T14:15:02Z
dc.date.issued 2019-04
dc.identifier.citation Abudahab , K , Prada , J M , Yang , Z , Bentley , S D , Croucher , N J , Corander , J & Aanensen , D M 2019 , ' PANINI : Pangenome Neighbour Identification for Bacterial Populations ' , Microbial Genomics , vol. 5 , no. 4 , 000220 . https://doi.org/10.1099/mgen.0.000220 en
dc.identifier.issn 2057-5858
dc.identifier.other PURE: 124892311
dc.identifier.other PURE UUID: 33190755-cd79-4d65-a918-a6f295fad3f1
dc.identifier.other WOS: 000466582400001
dc.identifier.uri http://hdl.handle.net/10138/302237
dc.description.abstract The standard workhorse for genomic analysis of the evolution of bacterial populations is phylogenetic modelling of mutations in the core genome. However, a notable amount of information about evolutionary and transmission processes in diverse populations can be lost unless the accessory genome is also taken into consideration. Here, we introduce PANINI (Pangenome Neighbour Identification for Bacterial Populations), a computationally scalable method for identifying the neighbours for each isolate in a data set using unsupervised machine learning with stochastic neighbour embedding based on the t-SNE (t-distributed stochastic neighbour embedding) algorithm. PANINI is browser-based and integrates with the Microreact platform for rapid online visualization and exploration of both core and accessory genome evolutionary signals, together with relevant epidemiological, geographical, temporal and other metadata. Several case studies with single- and multi-clone pneumococcal populations are presented to demonstrate the ability to identify biologically important signals from gene content data. PANINI is available at http://panini.pathogen.watch and code at http://gitlab.com/cgps/panini. en
dc.format.extent 10
dc.language.iso eng
dc.relation.ispartof Microbial Genomics
dc.rights en
dc.subject pangenome en
dc.subject microbial population genomics en
dc.subject machine learning en
dc.subject web application en
dc.subject STREPTOCOCCUS-PNEUMONIAE en
dc.subject EVOLUTION en
dc.subject 111 Mathematics en
dc.subject 318 Medical biotechnology en
dc.title PANINI : Pangenome Neighbour Identification for Bacterial Populations en
dc.type Article
dc.description.version Peer reviewed
dc.identifier.doi https://doi.org/10.1099/mgen.0.000220
dc.type.uri info:eu-repo/semantics/other
dc.type.uri info:eu-repo/semantics/publishedVersion
dc.contributor.pbl
dc.contributor.pbl
dc.contributor.pbl
dc.contributor.pbl

Files in this item

Total number of downloads: Loading...

Files Size Format View
mgen000220.pdf 7.854Mb PDF View/Open

This item appears in the following Collection(s)

Show simple item record