EpiViz: an implementation of Circos plots for epidemiologists
Matt Lee, a PhD student from the University of Bristol, delivered a talk on the use of Circos plots in epidemiology.
Biological pathways involve numerous processes, but epidemiology studies predominantly focus on single exposure and single outcome associations. This is primarily because identifying meaningful intermediate associations that can be taken forward for further analysis is complex.
In his talk, Matt discussed how tools like EpiViz can be used to produce simple and efficient Circos plots for those new to programming and data visualisation. By giving people a tool that makes data visualisation easier to produce, epidemiologists can gain a better understanding of the results of complex epidemiological studies. Greater insight in to the results can help increase the impact of such studies.
Related papers
Matthew A Lee, George McMahon, Ville Karhunen, Kaitlin H Wade, Laura J Corbin, David A Hughes, George Davey Smith, Debbie A Lawlor, Marjo-Riitta Jarvelin, Nicholas J Timpson, Common variation at 16p11.2 is associated with glycosuria in pregnancy: findings from a genome-wide association study in European women, Human Molecular Genetics, Volume 29, Issue 12, 15 June 2020, Pages 2098–2106
A Statistician’s Botanical Garden - The Ideas behind Trees, Model-Based Trees and Random Forests
Classification and regression trees, model-based trees and random forests are powerful statistical methods from the field of machine learning. However, while individual trees are easy to interpret, random forests are "black box" prediction methods. Despite this, they provide variable importance measures, that are being used to judge the relevance of the individual predictor variables.
In this seminar, Professor Carolin Strobl introduced the rationale behind trees, model-based trees and random forests, and illustrated their potential for high-dimensional data exploration, while also pointing out limitations and potential pitfalls in their practical application.
Related papers
Fokkema, M., & Strobl, C. (2020). Fitting prediction rule ensembles to psychological research data: An introduction and tutorial. Psychological Methods, 25(5), 636–652.
Detecting the hierarchical structure of the cell nucleus
Chromatin consists of DNA wrapped around histones and forms complex three-dimensional structures within the cell nucleus with various degrees of compaction.
Genes have been shown to be repressed by their proximity to the nuclear periphery or activated by being in contact with special regulatory regions called enhancers. Thus the relative positioning of genes and their interactions with other regions are very important in determining whether they are expressed or not.
In this talk, Iona Olan from the University of Cambridge discussed her work on cellular senescence, a phenotype associated with dramatic changes in its chromatin interactions network relative to normal cells. Senescence corresponds to permanent cell cycle arrest and has been shown to act as a protective barrier against tumourigenesis.
Related papers
Kosuke Tomimatsu, Dóra Bihary, Ioana Olan, Aled Parry, Stefan Schoenfelder, Adelyne Chan, Guy Slater, Yoko Ito, Peter Rugg-Gunn, Kristina Kirschner, Camino Bermejo-Rodriguez, Masako Narita, Tomomi Seko, Hiroyuki Kugoh, Ken Shiraishi, Koji Sayama, Hiroshi Kimura, Peter Fraser, Shamith Samarajiwa, Masashi Narita, Locus-specific induction of gene expression from heterochromatin loci during cellular senescence, Nature Research, pre-print.
