Kelly, Catherine;
Szabo, Anita;
Pontikos, Nikolas;
Arno, Gavin;
Robinson, Peter N;
Jacobsen, Jules OB;
Smedley, Damian;
(2022)
Phenotype-aware prioritisation of rare Mendelian disease variants.
Trends in Genetics
, 38
(12)
pp. 1271-1283.
10.1016/j.tig.2022.07.002.
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Abstract
A molecular diagnosis from the analysis of sequencing data in rare Mendelian diseases has a huge impact on the management of patients and their families. Numerous patient phenotype-aware variant prioritisation (VP) tools have been developed to help automate this process, and shorten the diagnostic odyssey, but performance statistics on real patient data are limited. Here we identify, assess, and compare the performance of all up-to-date, freely available, and programmatically accessible tools using a whole-exome, retinal disease dataset from 134 individuals with a molecular diagnosis. All tools were able to identify around two-thirds of the genetic diagnoses as the top-ranked candidate, with LIRICAL performing best overall. Finally, we discuss the challenges to overcome most cases remaining undiagnosed after current, state-of-the-art practices.
Type: | Article |
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Title: | Phenotype-aware prioritisation of rare Mendelian disease variants |
Location: | England |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1016/j.tig.2022.07.002 |
Publisher version: | https://doi.org/10.1016/j.tig.2022.07.002 |
Language: | English |
Additional information: | © 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
Keywords: | molecular diagnosis, phenotype, rare disease, variant prioritisation, variant prioritization |
UCL classification: | UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Institute of Ophthalmology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL |
URI: | https://discovery.ucl.ac.uk/id/eprint/10153890 |
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