Structure_threader: An improved method for automation and parallelization of programs structure, fastStructure and MavericK on multicore CPU systems

Detalhes bibliográficos
Autor(a) principal: Pina-Martins, Francisco
Data de Publicação: 2017
Outros Autores: Silva, Diogo N., Fino, Joana, Paulo, Octávio S.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10451/43985
Resumo: Structure_threader is a program to parallelize multiple runs of genetic clustering software that does not make use of multithreading technology (structure, fastStructure and MavericK) on multicore computers. Our approach was benchmarked across multiple systems and displayed great speed improvements relative to the single-threaded implementation, scaling very close to linearly with the number of physical cores used. Structure_threader was compared to previous software written for the same task-ParallelStructure and StrAuto and was proven to be the faster (up to 25% faster) wrapper under all tested scenarios. Furthermore, Structure_threader can perform several automatic and convenient operations, assisting the user in assessing the most biologically likely value of 'K' via implementations such as the "Evanno," or "Thermodynamic Integration" tests and automatically draw the "meanQ" plots (static or interactive) for each value of K (or even combined plots). Structure_threader is written in python 3 and licensed under the GPLv3. It can be downloaded free of charge at https://github.com/StuntsPT/Structure_threader.
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spelling Structure_threader: An improved method for automation and parallelization of programs structure, fastStructure and MavericK on multicore CPU systemsComputational BiologyGenotyping TechniquesCluster AnalysisSoftwareStructure_threader is a program to parallelize multiple runs of genetic clustering software that does not make use of multithreading technology (structure, fastStructure and MavericK) on multicore computers. Our approach was benchmarked across multiple systems and displayed great speed improvements relative to the single-threaded implementation, scaling very close to linearly with the number of physical cores used. Structure_threader was compared to previous software written for the same task-ParallelStructure and StrAuto and was proven to be the faster (up to 25% faster) wrapper under all tested scenarios. Furthermore, Structure_threader can perform several automatic and convenient operations, assisting the user in assessing the most biologically likely value of 'K' via implementations such as the "Evanno," or "Thermodynamic Integration" tests and automatically draw the "meanQ" plots (static or interactive) for each value of K (or even combined plots). Structure_threader is written in python 3 and licensed under the GPLv3. It can be downloaded free of charge at https://github.com/StuntsPT/Structure_threader.Repositório da Universidade de LisboaPina-Martins, FranciscoSilva, Diogo N.Fino, JoanaPaulo, Octávio S.2020-07-13T17:10:57Z20172017-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10451/43985eng10.1111/1755-0998.12702info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-11-20T17:59:05Zoai:repositorio.ul.pt:10451/43985Portal AgregadorONGhttps://www.rcaap.pt/oai/openairemluisa.alvim@gmail.comopendoar:71602024-11-20T17:59:05Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Structure_threader: An improved method for automation and parallelization of programs structure, fastStructure and MavericK on multicore CPU systems
title Structure_threader: An improved method for automation and parallelization of programs structure, fastStructure and MavericK on multicore CPU systems
spellingShingle Structure_threader: An improved method for automation and parallelization of programs structure, fastStructure and MavericK on multicore CPU systems
Pina-Martins, Francisco
Computational Biology
Genotyping Techniques
Cluster Analysis
Software
title_short Structure_threader: An improved method for automation and parallelization of programs structure, fastStructure and MavericK on multicore CPU systems
title_full Structure_threader: An improved method for automation and parallelization of programs structure, fastStructure and MavericK on multicore CPU systems
title_fullStr Structure_threader: An improved method for automation and parallelization of programs structure, fastStructure and MavericK on multicore CPU systems
title_full_unstemmed Structure_threader: An improved method for automation and parallelization of programs structure, fastStructure and MavericK on multicore CPU systems
title_sort Structure_threader: An improved method for automation and parallelization of programs structure, fastStructure and MavericK on multicore CPU systems
author Pina-Martins, Francisco
author_facet Pina-Martins, Francisco
Silva, Diogo N.
Fino, Joana
Paulo, Octávio S.
author_role author
author2 Silva, Diogo N.
Fino, Joana
Paulo, Octávio S.
author2_role author
author
author
dc.contributor.none.fl_str_mv Repositório da Universidade de Lisboa
dc.contributor.author.fl_str_mv Pina-Martins, Francisco
Silva, Diogo N.
Fino, Joana
Paulo, Octávio S.
dc.subject.por.fl_str_mv Computational Biology
Genotyping Techniques
Cluster Analysis
Software
topic Computational Biology
Genotyping Techniques
Cluster Analysis
Software
description Structure_threader is a program to parallelize multiple runs of genetic clustering software that does not make use of multithreading technology (structure, fastStructure and MavericK) on multicore computers. Our approach was benchmarked across multiple systems and displayed great speed improvements relative to the single-threaded implementation, scaling very close to linearly with the number of physical cores used. Structure_threader was compared to previous software written for the same task-ParallelStructure and StrAuto and was proven to be the faster (up to 25% faster) wrapper under all tested scenarios. Furthermore, Structure_threader can perform several automatic and convenient operations, assisting the user in assessing the most biologically likely value of 'K' via implementations such as the "Evanno," or "Thermodynamic Integration" tests and automatically draw the "meanQ" plots (static or interactive) for each value of K (or even combined plots). Structure_threader is written in python 3 and licensed under the GPLv3. It can be downloaded free of charge at https://github.com/StuntsPT/Structure_threader.
publishDate 2017
dc.date.none.fl_str_mv 2017
2017-01-01T00:00:00Z
2020-07-13T17:10:57Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10451/43985
url http://hdl.handle.net/10451/43985
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1111/1755-0998.12702
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv mluisa.alvim@gmail.com
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