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European Journal of Human Genetics
Article . 2022 . Peer-reviewed
License: CC BY
Data sources: Crossref
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DIGITAL.CSIC
Article . 2023 . Peer-reviewed
Data sources: DIGITAL.CSIC
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UCL Discovery
Article . 2022
Data sources: UCL Discovery
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Assessing the digenic model in rare disorders using population sequencing data

Authors: Nerea Moreno-Ruiz; J. C. Ambrose; P. Arumugam; E. L. Baple; M. Bleda; F. Boardman-Pretty; J. M. Boissiere; +78 Authors

Assessing the digenic model in rare disorders using population sequencing data

Abstract

AbstractAn 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.

Countries
United Kingdom, Spain
Keywords

Multifactorial Inheritance, Population genetics, Genetic interaction, Diseases, Sequence Analysis, DNA, Brief Communication, Rare Diseases, Genomics England Research Consortium, Exome Sequencing, Humans, Exome

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
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7
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64
62
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