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https://hdl.handle.net/1959.11/14595
Full metadata record
DC Field | Value | Language |
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dc.contributor.author | Gondro, Cedric | en |
dc.contributor.author | Porto-Neto, Laercio R | en |
dc.contributor.author | Lee, S H | en |
local.source.editor | Editor(s): Cedric Gondro, Julius van der Werf, Ben Hayes | en |
dc.date.accessioned | 2014-04-08T11:23:00Z | - |
dc.date.issued | 2013 | - |
dc.identifier.citation | Genome-Wide Association Studies and Genomic Predictions, p. 1-17 | en |
dc.identifier.isbn | 9781627034470 | en |
dc.identifier.isbn | 9781627034463 | en |
dc.identifier.uri | https://hdl.handle.net/1959.11/14595 | - |
dc.description.abstract | In recent years R has become de facto statistical programming language of choice for statisticians and it is also arguably the most widely used generic environment for analysis of high-throughput genomic data. In this chapter we discuss some approaches to improve performance of R when working with large SNP datasets. | en |
dc.language | en | en |
dc.publisher | Humana Press | en |
dc.relation.ispartof | Genome-Wide Association Studies and Genomic Predictions | en |
dc.relation.ispartofseries | Methods in Molecular Biology | en |
dc.relation.isversionof | 1 | en |
dc.title | R for Genome-Wide Association Studies | en |
dc.type | Book Chapter | en |
dc.identifier.doi | 10.1007/978-1-62703-447-0_1 | en |
dc.subject.keywords | Quantitative Genetics (incl Disease and Trait Mapping Genetics) | en |
local.contributor.firstname | Cedric | en |
local.contributor.firstname | Laercio R | en |
local.contributor.firstname | S H | en |
local.subject.for2008 | 060412 Quantitative Genetics (incl Disease and Trait Mapping Genetics) | en |
local.subject.seo2008 | 970106 Expanding Knowledge in the Biological Sciences | en |
local.profile.school | School of Environmental and Rural Science | en |
local.profile.school | Animal Science | en |
local.profile.school | Animal Science | en |
local.profile.email | cgondro2@une.edu.au | en |
local.output.category | B1 | en |
local.record.place | au | en |
local.record.institution | University of New England | en |
local.identifier.epublicationsrecord | une-20130829-122010 | en |
local.publisher.place | New York, United States of America | en |
local.identifier.totalchapters | 26 | en |
local.format.startpage | 1 | en |
local.format.endpage | 17 | en |
local.series.issn | 1940-6029 | en |
local.series.issn | 1064-3745 | en |
local.series.number | 1019 | en |
local.contributor.lastname | Gondro | en |
local.contributor.lastname | Porto-Neto | en |
local.contributor.lastname | Lee | en |
dc.identifier.staff | une-id:cgondro2 | en |
dc.identifier.staff | une-id:lportone | en |
local.profile.orcid | 0000-0003-0666-656X | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.identifier.unepublicationid | une:14810 | en |
dc.identifier.academiclevel | Academic | en |
local.title.maintitle | R for Genome-Wide Association Studies | en |
local.output.categorydescription | B1 Chapter in a Scholarly Book | en |
local.relation.url | http://trove.nla.gov.au/version/198468706 | en |
local.search.author | Gondro, Cedric | en |
local.search.author | Porto-Neto, Laercio R | en |
local.search.author | Lee, S H | en |
local.uneassociation | Unknown | en |
local.year.published | 2013 | en |
local.subject.for2020 | 310506 Gene mapping | en |
local.subject.seo2020 | 280102 Expanding knowledge in the biological sciences | en |
Appears in Collections: | Book Chapter |
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