Guillot, Gilles Olsson, Maja Benson, Mikael Rudemo, Mats
Comparison of gene expression for two groups of individuals form an important subclass of microarray experiments. We study multivariate procedures, in particular use of Hotelling’s T2 for discrimination between the groups with a special emphasis on methods based on few genes only. We apply the methods to data from an experiment with a group of atop...
Wilhelm-Benartzi, C S Koestler, D C Karagas, M R Flanagan, J M Christensen, B C Kelsey, K T Marsit, C J Houseman, E A Brown, R
Published in
British journal of cancer
The promise of epigenome-wide association studies and cancer-specific somatic DNA methylation changes in improving our understanding of cancer, coupled with the decreasing cost and increasing coverage of DNA methylation microarrays, has brought about a surge in the use of these technologies. Here, we aim to provide both a review of issues encounter...
Mensaert, Klaas Denil, Simon Trooskens, Geert Van Criekinge, Wim Thas, Olivier De Meyer, Tim
Published in
Environmental and molecular mutagenesis
Epigenetics refers to the collection of heritable features that modulate the genome-environment interaction without being encoded in the actual DNA sequence. While being mitotically and sometimes even meiotically transmitted, epigenetic traits often demonstrate extensive flexibility. This allows cells to acquire diverse gene expression patterns dur...
Boelens, Ruth De Wever, Bram Rosseel, Yves Verstraete, Alain G Derese, Anselme
Published in
BMC Medical Education
BackgroundIn problem-based learning, a tutor, the quality of the problems and group functioning play a central role in stimulating student learning. This study is conducted in a hybrid medical curriculum where problem-based learning is one of the pedagogical approaches. The aim of this study was to examine which tutor tasks are the most important d...
Roels, S P Bossier, H Loeys, T Moerkerke, B
Published in
Journal of neuroscience methods
Data-analytical stability is an important additional criterion that can easily be incorporated in evaluation protocols.
De Neve, Debbie Devos, Geert Tuytens, Melissa
Fabre, Anne-Claire Bickford, David Segall, Marion Herrel, Anthony
International audience
Brooks, Mollie Elizabeth Kristensen, Kasper van Benthem, Koen J. Magnusson, Arni Berg, Casper Willestofte Nielsen, Anders Skaug, Hans J. Machler, Martin Bolker, Benjamin M.
Count data can be analyzed using generalized linear mixed models when observations are correlated in ways that require random effects. However, count data are often zero-inflated, containing more zeros than would be expected from the typical error distributions. We present a new package, glmmTMB, and compare it to other R packages that fit zero-inf...
Brooks, Mollie Elizabeth Kristensen, Kasper van Benthem, Koen J. Magnusson, Arni Berg, Casper Willestofte Nielsen, Anders Skaug, Hans J. Machler, Martin Bolker, Benjamin M.
Count data can be analyzed using generalized linear mixed models when observations are correlated in ways that require random effects. However, count data are often zero-inflated, containing more zeros than would be expected from the typical error distributions. We present a new package, glmmTMB, and compare it to other R packages that fit zero-inf...
Brooks, Mollie Elizabeth Kristensen, Kasper van Benthem, Koen J. Magnusson, Arni Berg, Casper Willestofte Nielsen, Anders Skaug, Hans J. Machler, Martin Bolker, Benjamin M.
Count data can be analyzed using generalized linear mixed models when observations are correlated in ways that require random effects. However, count data are often zero-inflated, containing more zeros than would be expected from the typical error distributions. We present a new package, glmmTMB, and compare it to other R packages that fit zero-inf...