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dc.contributor.authorGasparini, Mauroen_US
dc.contributor.authorRockstroh, Anjaen_US
dc.contributor.authorWells, Christineen_US
dc.contributor.authorKennedy, Dereken_US
dc.contributor.editorEditor exceeds RIMS limiten_US
dc.date.accessioned2017-05-03T11:12:32Z
dc.date.available2017-05-03T11:12:32Z
dc.date.issued2011en_US
dc.date.modified2012-03-22T01:16:58Z
dc.identifier.urihttp://hdl.handle.net/10072/43883
dc.description.abstractThe G3BP2 locus has been discovered and studied in [1]. In a recent set of quantitative reverse transcription polymerase chain reaction (qRT-PCR) experiments, we have been trying to study the G3BP2 transcripts and their relationships with their genomic neighborhood. The gene expression experiments we set up involved normalizing housekeeping genes, several different transcripts, several conditions of interest (different cell lines, tumor versus normal tissue), technical replicates, missing data and small sample sizes in all resulting cells. The scenario is suitable for the analysis via Bayesian hierarchical models using as response variable the continuous interpolation of cycles in the qRT-PCR, which is naturally taken to be lognormal. The construction of few normal hierarchical models will be discussed, critical points will be illustrated and a comparison with standard methods will be made. Currently, the state of the art in analysing qRT-PCR data is based on ad hoc user-friendly software (such as REST) or on linear mixed models. We will show how the alternative analysis based on statistical Bayesian networks can be flexible enough to address the important issue of estimating gene-gene interactions.en_US
dc.description.publicationstatusYesen_US
dc.languageEnglishen_US
dc.publisherInternationale Biometrische Gesellschaft, Region Austria-Switzerlanden_US
dc.publisher.placeSwitzerlanden_US
dc.relation.ispartofstudentpublicationNen_US
dc.relation.ispartofconferencenameCEN 2011 Bridging Biostatistical Theory and Applicationen_US
dc.relation.ispartofconferencetitleGenetics and Biomarkeren_US
dc.relation.ispartofdatefrom2011-09-12en_US
dc.relation.ispartofdateto2011-09-16en_US
dc.relation.ispartoflocationZurich, Switzerlanden_US
dc.rights.retentionYen_US
dc.subject.fieldofresearchBiostatisticsen_US
dc.subject.fieldofresearchGenome Structure and Regulationen_US
dc.subject.fieldofresearchcode010402en_US
dc.subject.fieldofresearchcode060407en_US
dc.titleAnalysis of small-sample gene expression and gene interactions via Bayesian hierarchical models Bridging Biostatistical Theory and Applicationen_US
dc.typeConference outputen_US
dc.type.descriptionE3 - Conference Publications (Extract Paper)en_US
dc.type.codeE - Conference Publicationsen_US
gro.date.issued2011
gro.hasfulltextNo Full Text
gro.griffith.authorKennedy, Derek D.


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    Contains papers delivered by Griffith authors at national and international conferences.

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