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Article: Bayesian detection of embryonic gene expression onset in C. elegans

TitleBayesian detection of embryonic gene expression onset in C. elegans
Authors
Keywords4D confocal microscopy
Embryonic onset
Change point detection
Bayesian method
Issue Date2015
PublisherInstitute of Mathematical Statistics. The Journal's web site is located at http://www.imstat.org/aoas/
Citation
The Annals of Applied Statistics, 2015, v. 9 n. 2, p. 950-968 How to Cite?
AbstractTo study how a zygote develops into an embryo with different tissues, large-scale 4D confocal movies of C. elegans embryos have been produced recently by experimental biologists. However, the lack of principled statistical methods for the highly noisy data has hindered the comprehensive analysis of these data sets. We introduced a probabilistic change point model on the cell lineage tree to estimate the embryonic gene expression onset time. A Bayesian approach is used to fit the 4D confocal movies data to the model. Subsequent classification methods are used to decide a model selection threshold and further refine the expression onset time from the branch level to the specific cell time level. Extensive simulations have shown the high accuracy of our method. Its application on real data yields both previously known results and new findings.
Persistent Identifierhttp://hdl.handle.net/10722/215089
ISSN
2019 Impact Factor: 1.675
2015 SCImago Journal Rankings: 1.533
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorHu, J-
dc.contributor.authorZhao, Z-
dc.contributor.authorYalamanchili, HK-
dc.contributor.authorWang, JJ-
dc.contributor.authorYe, K-
dc.contributor.authorFan, X-
dc.date.accessioned2015-08-21T12:26:22Z-
dc.date.available2015-08-21T12:26:22Z-
dc.date.issued2015-
dc.identifier.citationThe Annals of Applied Statistics, 2015, v. 9 n. 2, p. 950-968-
dc.identifier.issn1932-6157-
dc.identifier.urihttp://hdl.handle.net/10722/215089-
dc.description.abstractTo study how a zygote develops into an embryo with different tissues, large-scale 4D confocal movies of C. elegans embryos have been produced recently by experimental biologists. However, the lack of principled statistical methods for the highly noisy data has hindered the comprehensive analysis of these data sets. We introduced a probabilistic change point model on the cell lineage tree to estimate the embryonic gene expression onset time. A Bayesian approach is used to fit the 4D confocal movies data to the model. Subsequent classification methods are used to decide a model selection threshold and further refine the expression onset time from the branch level to the specific cell time level. Extensive simulations have shown the high accuracy of our method. Its application on real data yields both previously known results and new findings.-
dc.languageeng-
dc.publisherInstitute of Mathematical Statistics. The Journal's web site is located at http://www.imstat.org/aoas/-
dc.relation.ispartofThe Annals of Applied Statistics-
dc.rights© Institute of Mathematical Statistics, 2015. This article is available online at https://doi.org/10.1214/15-AOAS820-
dc.subject4D confocal microscopy-
dc.subjectEmbryonic onset-
dc.subjectChange point detection-
dc.subjectBayesian method-
dc.titleBayesian detection of embryonic gene expression onset in C. elegans-
dc.typeArticle-
dc.identifier.emailWang, JJ: junwen@hku.hk-
dc.identifier.authorityWang, JJ=rp00280-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1214/15-AOAS820-
dc.identifier.scopuseid_2-s2.0-84938544438-
dc.identifier.hkuros246636-
dc.identifier.volume9-
dc.identifier.issue2-
dc.identifier.spage950-
dc.identifier.epage968-
dc.identifier.isiWOS:000358368000019-
dc.publisher.placeUnited States-
dc.identifier.issnl1932-6157-

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