Affiliation:
1. Department of Medical Genetics, Oslo University Hospital and University of Oslo , 0424 Oslo, Norway
2. Department of Forensic Sciences, Oslo University Hospital , 0424 Oslo, Norway
Abstract
Abstract
Motivation
Cosegregation analysis is a powerful tool for identifying pathogenic genetic variants, but its implementation remains challenging. Existing software is either limited in scope or too demanding for many end users. Moreover, current solutions lack methods for assessing the robustness of cosegregation evidence, which is important due to its reliance on uncertain estimates.
Results
We present shinyseg, a comprehensive web application for clinical cosegregation analysis. Our app streamlines penetrance specification based on either liability classes or epidemiological data such as risks, hazard ratios, and age of onset distribution. In addition, it incorporates sensitivity analyses to assess the robustness of cosegregation evidence, and offers support in clinical interpretation.
Availability and implementation
The shinyseg app is freely available at https://chrcarrizosa.shinyapps.io/shinyseg, with documentation and complete R source code on https://chrcarrizosa.github.io/shinyseg and https://github.com/chrcarrizosa/shinyseg.
Funder
Research Council of Norway
Publisher
Oxford University Press (OUP)
Cited by
1 articles.
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