Network-based methods for analyzing the genetics of human complexdiseases

Detalhes bibliográficos
Ano de defesa: 2017
Autor(a) principal: Gilderlanio Santana de Araújo
Orientador(a): Eduardo Martin Tarazona Santos
Banca de defesa: Não Informado pela instituição
Tipo de documento: Tese
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal de Minas Gerais
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Bioinformática
Link de acesso: http://hdl.handle.net/1843/BUOS-APSR9L
Resumo: ...
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spelling Eduardo Martin Tarazona SantosMaíra Ribeiro RodriguesGilderlanio Santana de Araújo2019-08-13T08:59:06Z2019-08-13T08:59:06Z2017-06-27http://hdl.handle.net/1843/BUOS-APSR9L...Interpreting the high volume of genomic data is a challenge for epidemiologists, anthropologists and geneticists that aim to understand the genetic basis of populations and phenotype variations (diseases/traits). In this respect, several computational methodsand tools have been developed to extract knowledge and data patterns from publicomic data for a diverse set of populations in genetic studies, and also to deal with transparency and reproducibility that has been two subjects of high importance in science. The genetic architecture of parental populations, such as African, European and Asian, has been subject of studies to understand the process of population structureand the origins of genetic diseases. It is well known that allele frequency and allele differentiation based on genotype data reveal hallmarks of dierential demographic history in worldwide populations, and some alleles are risk variants that confer disease risk and their frequency may lead to varying susceptibility to complex diseases. In this context, this thesis has two main contributions, one is a network-based approach to integrate and visualize data from NGHRI/EBI GWAS Catalog and 1000 Genomes Project, and the second is scientific workflow approach to disclose scientific knowledge. First, we present DANCE (Disease-Ancestry Network), a new web tool to improve the understanding of the genetic architecture of diseases in a cross-ethnic view. DANCE is a tool to integrate, summarize and visualize molecular profiles of genetic disease associations in a network-based approach. It was implemented as a web-based tool to explore genetic associations and risk allele dierentiation across global populations to support a broad set of genetic population analyses, such as GWAS replication and admixture mapping. Our networks are bipartite, where nodes are either phenotypes (diseases/traits) or SNPs and diseases are connected to SNPs if there is a known association in current GWAS studies. In a graphical projection, the population variability of risk-alleles frequencies is represented as a color gradient based on the pairwise FST values of dierent populations, where higher values point out highly dierentiated SNPs between the two populations. In addition, this study presents the EPIGEN Scientific Workflow (EPIGEN-SW), which aims to improve transparency and reproducibility in genetic and epidemiology studies.The EPIGEN-SW is implemented as a web tool and facilitates the access to computational resources through an integrative and interactive approach based on flowcharts, masterscripts and auxiliary scripts. Both approaches are implemented as web tools and made freely available for the scientific community. DANCE are available online at www.ldgh.com.br/dance and the EPIGEN-Brazil Scientific Workflow is available at www.ldgh.com.br/scientificworkflow.Universidade Federal de Minas GeraisUFMGBioinformáticaBioinformáticaNetwork-based methods for analyzing the genetics of human complexdiseasesinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisinfo:eu-repo/semantics/openAccessporreponame:Repositório Institucional da UFMGinstname:Universidade Federal de Minas Gerais (UFMG)instacron:UFMGORIGINALgilderlaniosaraujo_tese.pdfapplication/pdf19391029https://repositorio.ufmg.br/bitstream/1843/BUOS-APSR9L/1/gilderlaniosaraujo_tese.pdfa2d505b966cd7f061da1ccf3576efb57MD51TEXTgilderlaniosaraujo_tese.pdf.txtgilderlaniosaraujo_tese.pdf.txtExtracted texttext/plain161213https://repositorio.ufmg.br/bitstream/1843/BUOS-APSR9L/2/gilderlaniosaraujo_tese.pdf.txtc5085247dfec1cfdcd0b16f9726b4990MD521843/BUOS-APSR9L2019-11-14 22:13:45.294oai:repositorio.ufmg.br:1843/BUOS-APSR9LRepositório de PublicaçõesPUBhttps://repositorio.ufmg.br/oaiopendoar:2019-11-15T01:13:45Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)false
dc.title.pt_BR.fl_str_mv Network-based methods for analyzing the genetics of human complexdiseases
title Network-based methods for analyzing the genetics of human complexdiseases
spellingShingle Network-based methods for analyzing the genetics of human complexdiseases
Gilderlanio Santana de Araújo
Bioinformática
Bioinformática
title_short Network-based methods for analyzing the genetics of human complexdiseases
title_full Network-based methods for analyzing the genetics of human complexdiseases
title_fullStr Network-based methods for analyzing the genetics of human complexdiseases
title_full_unstemmed Network-based methods for analyzing the genetics of human complexdiseases
title_sort Network-based methods for analyzing the genetics of human complexdiseases
author Gilderlanio Santana de Araújo
author_facet Gilderlanio Santana de Araújo
author_role author
dc.contributor.advisor1.fl_str_mv Eduardo Martin Tarazona Santos
dc.contributor.advisor-co1.fl_str_mv Maíra Ribeiro Rodrigues
dc.contributor.author.fl_str_mv Gilderlanio Santana de Araújo
contributor_str_mv Eduardo Martin Tarazona Santos
Maíra Ribeiro Rodrigues
dc.subject.por.fl_str_mv Bioinformática
topic Bioinformática
Bioinformática
dc.subject.other.pt_BR.fl_str_mv Bioinformática
description ...
publishDate 2017
dc.date.issued.fl_str_mv 2017-06-27
dc.date.accessioned.fl_str_mv 2019-08-13T08:59:06Z
dc.date.available.fl_str_mv 2019-08-13T08:59:06Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/doctoralThesis
format doctoralThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/1843/BUOS-APSR9L
url http://hdl.handle.net/1843/BUOS-APSR9L
dc.language.iso.fl_str_mv por
language por
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Universidade Federal de Minas Gerais
dc.publisher.initials.fl_str_mv UFMG
publisher.none.fl_str_mv Universidade Federal de Minas Gerais
dc.source.none.fl_str_mv reponame:Repositório Institucional da UFMG
instname:Universidade Federal de Minas Gerais (UFMG)
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instacron_str UFMG
institution UFMG
reponame_str Repositório Institucional da UFMG
collection Repositório Institucional da UFMG
bitstream.url.fl_str_mv https://repositorio.ufmg.br/bitstream/1843/BUOS-APSR9L/1/gilderlaniosaraujo_tese.pdf
https://repositorio.ufmg.br/bitstream/1843/BUOS-APSR9L/2/gilderlaniosaraujo_tese.pdf.txt
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