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However, conventional approaches to association analyses lack statistical power for uncovering weak effects, therefore the locations of hotspots on the human genome remain, to date, largely unknown.
H\u00e9l\u00e8ne Ruffieux\u2019s project develops a principled statistical framework to (1) describe an \u201catlas\u201d of hotspots on the human genome for the healthy population and for specific disease areas (such as autoimmune and infectious diseases), and (2) use this atlas as an anchor to study the disruption of molecular networks when disease occurs. Specifically, it proposes graphical and sparse regression approaches in the Bayesian setting for the joint modelling of quantitative trait locus (QTL) effects and of their mediation mechanisms. It also pays special attention to tailoring algorithms to the complex high-dimensional nature of molecular data, to produce robust, scalable and interpretable inferences. H\u00e9l\u00e8ne Ruffieux and her team carry this research at the MRC Biostatistics Unit of the University of Cambridge, in collaboration with research institutes in biology, data science, mathematics and medicine.<\/p>\n
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H\u00e9l\u00e8ne Ruffieux (EPFL 2020) An atlas of genetic hotspots to disentangle the molecular networks underlying complex diseasesExploring the genetic bases of human diseases has become a critical step towards predicting health outcomes and developing effective therapies. It has been suggested that the risk and progression of most complex diseases may be largely driven by hotspot […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"1080","footnotes":""},"categories":[],"tags":[],"class_list":["post-871","post","type-post","status-publish","format-standard","hentry"],"acf":[],"yoast_head":"\n