UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Assessing the digenic model in rare disorders using population sequencing data

Moreno-Ruiz, N; Ambrose, JC; Arumugam, P; Baple, EL; Bleda, M; Boardman-Pretty, F; Boissiere, JM; ... Casals, F; + view all (2022) Assessing the digenic model in rare disorders using population sequencing data. European Journal of Human Genetics 10.1038/s41431-022-01191-x. (In press). Green open access

[thumbnail of Ryten_Assessing the digenic model in rare disorders using population sequencing data_AOP.pdf]
Preview
Text
Ryten_Assessing the digenic model in rare disorders using population sequencing data_AOP.pdf - Published Version

Download (600kB) | Preview

Abstract

An important fraction of patients with rare disorders remains with no clear genetic diagnostic, even after whole-exome or whole-genome sequencing, posing a difficulty in giving adequate treatment and genetic counseling. The analysis of genomic data in rare disorders mostly considers the presence of single gene variants in coding regions that follow a concrete monogenic mode of inheritance. A digenic inheritance, with variants in two functionally-related genes in the same individual, is a plausible alternative that might explain the genetic basis of the disease in some cases. In this case, digenic disease combinations should be absent or underrepresented in healthy individuals. We develop a framework to evaluate the significance of digenic combinations and test its statistical power in different scenarios. We suggest that this approach will be relevant with the advent of new sequencing efforts including hundreds of thousands of samples.

Type: Article
Title: Assessing the digenic model in rare disorders using population sequencing data
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1038/s41431-022-01191-x
Publisher version: https://doi.org/10.1038/s41431-022-01191-x
Language: English
Additional information: This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third-party material in this article are included in the Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
Keywords: Genomics England Research Consortium
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health > Genetics and Genomic Medicine Dept
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
URI: https://discovery.ucl.ac.uk/id/eprint/10158400
Downloads since deposit
11Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item