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dc.contributor.authorMai, The T
dc.contributor.authorTurner, Paul
dc.contributor.authorCorander, Jukka
dc.date.accessioned2021-03-30T05:02:05Z
dc.date.available2021-03-30T05:02:05Z
dc.date.issued2021
dc.identifier.citationBMC Bioinformatics. 2021 Mar 27;22(1):164
dc.identifier.urihttp://hdl.handle.net/10852/85052
dc.description.abstractBackground Heritability is a central measure in genetics quantifying how much of the variability observed in a trait is attributable to genetic differences. Existing methods for estimating heritability are most often based on random-effect models, typically for computational reasons. The alternative of using a fixed-effect model has received much more limited attention in the literature. Results In this paper, we propose a generic strategy for heritability inference, termed as “boosting heritability”, by combining the advantageous features of different recent methods to produce an estimate of the heritability with a high-dimensional linear model. Boosting heritability uses in particular a multiple sample splitting strategy which leads in general to a stable and accurate estimate. We use both simulated data and real antibiotic resistance data from a major human pathogen, Sptreptococcus pneumoniae, to demonstrate the attractive features of our inference strategy. Conclusions Boosting is shown to offer a reliable and practically useful tool for inference about heritability.
dc.language.isoeng
dc.rightsThe Author(s)
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.titleBoosting heritability: estimating the genetic component of phenotypic variation with multiple sample splitting
dc.typeJournal article
dc.date.updated2021-03-30T05:02:08Z
dc.creator.authorMai, The T
dc.creator.authorTurner, Paul
dc.creator.authorCorander, Jukka
dc.identifier.cristin1908220
dc.identifier.doihttps://doi.org/10.1186/s12859-021-04079-7
dc.identifier.urnURN:NBN:no-87721
dc.type.documentTidsskriftartikkel
dc.type.peerreviewedPeer reviewed
dc.identifier.fulltextFulltext https://www.duo.uio.no/bitstream/handle/10852/85052/1/12859_2021_Article_4079.pdf
dc.type.versionPublishedVersion
cristin.articleid164


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