A flexible computational pipeline for research analyses of unsolved clinical exome cases
Abstract Exome sequencing has enabled molecular diagnoses for rare disease patients but often with initial diagnostic rates of ~25−30%. Here we develop a robust computational pipeline to rank variants for reassessment of unsolved rare disease patients. A comprehensive web-based patient report is gen...
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Nature Portfolio
2020
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oai:doaj.org-article:811cb355cf5b4897b431fd467c9f37522021-12-02T16:18:09ZA flexible computational pipeline for research analyses of unsolved clinical exome cases10.1038/s41525-020-00161-w2056-7944https://doaj.org/article/811cb355cf5b4897b431fd467c9f37522020-12-01T00:00:00Zhttps://doi.org/10.1038/s41525-020-00161-whttps://doaj.org/toc/2056-7944Abstract Exome sequencing has enabled molecular diagnoses for rare disease patients but often with initial diagnostic rates of ~25−30%. Here we develop a robust computational pipeline to rank variants for reassessment of unsolved rare disease patients. A comprehensive web-based patient report is generated in which all deleterious variants can be filtered by gene, variant characteristics, OMIM disease and Phenolyzer scores, and all are annotated with an ACMG classification and links to ClinVar. The pipeline ranked 21/34 previously diagnosed variants as top, with 26 in total ranked ≤7th, 3 ranked ≥13th; 5 failed the pipeline filters. Pathogenic/likely pathogenic variants by ACMG criteria were identified for 22/145 unsolved cases, and a previously undefined candidate disease variant for 27/145. This open access pipeline supports the partnership between clinical and research laboratories to improve the diagnosis of unsolved exomes. It provides a flexible framework for iterative developments to further improve diagnosis.Timo LassmannRichard W. FrancisAlexia WeeksDave TangSarra E. JamiesonStephanie BroleyHugh J. S. DawkinsLauren DreyerJack GoldblattTudor GrozaBenjamin KamienCathy Kiraly-BorriFiona McKenzieLesley MurphyNicholas PachterGargi PathakCathryn PoultonAmanda SamanekRachel SkossJennie SleeSharron TownshendMichelle WardGareth S. BaynamJenefer M. BlackwellNature PortfolioarticleMedicineRGeneticsQH426-470ENnpj Genomic Medicine, Vol 5, Iss 1, Pp 1-11 (2020) |
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DOAJ |
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DOAJ |
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EN |
| topic |
Medicine R Genetics QH426-470 |
| spellingShingle |
Medicine R Genetics QH426-470 Timo Lassmann Richard W. Francis Alexia Weeks Dave Tang Sarra E. Jamieson Stephanie Broley Hugh J. S. Dawkins Lauren Dreyer Jack Goldblatt Tudor Groza Benjamin Kamien Cathy Kiraly-Borri Fiona McKenzie Lesley Murphy Nicholas Pachter Gargi Pathak Cathryn Poulton Amanda Samanek Rachel Skoss Jennie Slee Sharron Townshend Michelle Ward Gareth S. Baynam Jenefer M. Blackwell A flexible computational pipeline for research analyses of unsolved clinical exome cases |
| description |
Abstract Exome sequencing has enabled molecular diagnoses for rare disease patients but often with initial diagnostic rates of ~25−30%. Here we develop a robust computational pipeline to rank variants for reassessment of unsolved rare disease patients. A comprehensive web-based patient report is generated in which all deleterious variants can be filtered by gene, variant characteristics, OMIM disease and Phenolyzer scores, and all are annotated with an ACMG classification and links to ClinVar. The pipeline ranked 21/34 previously diagnosed variants as top, with 26 in total ranked ≤7th, 3 ranked ≥13th; 5 failed the pipeline filters. Pathogenic/likely pathogenic variants by ACMG criteria were identified for 22/145 unsolved cases, and a previously undefined candidate disease variant for 27/145. This open access pipeline supports the partnership between clinical and research laboratories to improve the diagnosis of unsolved exomes. It provides a flexible framework for iterative developments to further improve diagnosis. |
| format |
article |
| author |
Timo Lassmann Richard W. Francis Alexia Weeks Dave Tang Sarra E. Jamieson Stephanie Broley Hugh J. S. Dawkins Lauren Dreyer Jack Goldblatt Tudor Groza Benjamin Kamien Cathy Kiraly-Borri Fiona McKenzie Lesley Murphy Nicholas Pachter Gargi Pathak Cathryn Poulton Amanda Samanek Rachel Skoss Jennie Slee Sharron Townshend Michelle Ward Gareth S. Baynam Jenefer M. Blackwell |
| author_facet |
Timo Lassmann Richard W. Francis Alexia Weeks Dave Tang Sarra E. Jamieson Stephanie Broley Hugh J. S. Dawkins Lauren Dreyer Jack Goldblatt Tudor Groza Benjamin Kamien Cathy Kiraly-Borri Fiona McKenzie Lesley Murphy Nicholas Pachter Gargi Pathak Cathryn Poulton Amanda Samanek Rachel Skoss Jennie Slee Sharron Townshend Michelle Ward Gareth S. Baynam Jenefer M. Blackwell |
| author_sort |
Timo Lassmann |
| title |
A flexible computational pipeline for research analyses of unsolved clinical exome cases |
| title_short |
A flexible computational pipeline for research analyses of unsolved clinical exome cases |
| title_full |
A flexible computational pipeline for research analyses of unsolved clinical exome cases |
| title_fullStr |
A flexible computational pipeline for research analyses of unsolved clinical exome cases |
| title_full_unstemmed |
A flexible computational pipeline for research analyses of unsolved clinical exome cases |
| title_sort |
flexible computational pipeline for research analyses of unsolved clinical exome cases |
| publisher |
Nature Portfolio |
| publishDate |
2020 |
| url |
https://doaj.org/article/811cb355cf5b4897b431fd467c9f3752 |
| work_keys_str_mv |
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| _version_ |
1718384178504925184 |