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Comparison of in silico strategies to prioritize rare genomic variants impacting RNA splicing for the diagnosis of genomic disorders.
- Source :
-
Scientific reports [Sci Rep] 2021 Oct 18; Vol. 11 (1), pp. 20607. Date of Electronic Publication: 2021 Oct 18. - Publication Year :
- 2021
-
Abstract
- The development of computational methods to assess pathogenicity of pre-messenger RNA splicing variants is critical for diagnosis of human disease. We assessed the capability of eight algorithms, and a consensus approach, to prioritize 249 variants of uncertain significance (VUSs) that underwent splicing functional analyses. The capability of algorithms to differentiate VUSs away from the immediate splice site as being 'pathogenic' or 'benign' is likely to have substantial impact on diagnostic testing. We show that SpliceAI is the best single strategy in this regard, but that combined usage of tools using a weighted approach can increase accuracy further. We incorporated prioritization strategies alongside diagnostic testing for rare disorders. We show that 15% of 2783 referred individuals carry rare variants expected to impact splicing that were not initially identified as 'pathogenic' or 'likely pathogenic'; one in five of these cases could lead to new or refined diagnoses.<br /> (© 2021. The Author(s).)
- Subjects :
- Algorithms
Databases, Genetic
Diagnosis
Diagnosis, Differential
Diagnostic Techniques and Procedures
Exons genetics
Genetic Variation genetics
Genomics methods
Humans
Mutation genetics
RNA Precursors genetics
RNA Splice Sites genetics
Computational Biology methods
Disease genetics
RNA Splicing genetics
Subjects
Details
- Language :
- English
- ISSN :
- 2045-2322
- Volume :
- 11
- Issue :
- 1
- Database :
- MEDLINE
- Journal :
- Scientific reports
- Publication Type :
- Academic Journal
- Accession number :
- 34663891
- Full Text :
- https://doi.org/10.1038/s41598-021-99747-2