BEGIN:VCALENDAR VERSION:2.0 PRODID:-//132.216.98.100//NONSGML kigkonsult.se iCalcreator 2.20.4// BEGIN:VEVENT UID:20250804T194341EDT-6962U3bh7W@132.216.98.100 DTSTAMP:20250804T234341Z DESCRIPTION:Aurélie Labbe\, PhD\n\nAssistant Professor\, Departments of Epi demiology\, Biostatistics & Occupational Health and Psychiatry\, 51³Ô¹ÏÍøUn iversity\n\nPrincipal component of explained variance\n\nALL ARE WELCOME\n \nAbstract:\n\nThe genomics era has led to an increase in the dimensionali ty of the data collected to investigate biological questions. In this cont ext\, dimension-reduction techniques can be used to summarize high-dimensi onal signals into low-dimensional ones\, to further test for association w ith one or more covariates of interest. We revisit one such approach\, pre viously known as Principal Component of Heritability and renamed here as P rincipal Component of Explained Variance (PCEV). As its name suggests\, th e PCEV seeks a linear combination of outcomes in an optimal manner\, by ma ximising the proportion of variance explained by one or several covariates of interest. By construction\, this\n\nmethod optimises power but limited by its computational complexity\, it has unfortunately received little at tention in the past. Here\, we propose a general analytical PCEV framework that builds on the assets of the original method\, i.e. conceptually simp le and free of tuning parameters. Moreover\, our framework extends the ran ge of applications of the original procedure by providing a computationall y simple strategy for high-dimensional outcomes\, along with exact and asy mptotic testing procedures that drastically reduce its computational cost. We investigate the merits of the\n\nPCEV using an extensive set of simula tions. Furthermore\, the use of the PCEV approach will be illustrated usin g three examples taken from the epigenetics and brain imaging areas.\n\nBi o:\n\nwww.medicine.mcgill.ca/epidemiology/labbe/\n\n \n\n \n DTSTART:20160322T193000Z DTEND:20160322T203000Z LOCATION:Room 24\, Purvis Hall\, CA\, QC\, Montreal\, H3A 1A2\, 1020 avenue des Pins Ouest SUMMARY:Biostatistics Seminar: 'Principal component of explained variance' URL:/epi-biostat-occh/channels/event/biostatistics-sem inar-principal-component-explained-variance-259540 END:VEVENT END:VCALENDAR