A flexible computational pipeline for research analyses of unsolved clinical exome cases

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 SleeSharron Townshend, Michelle Ward, Gareth S. Baynam, Jenefer M. Blackwell

Research output: Contribution to journalArticle

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.

Original languageEnglish
Article number54
Journalnpj Genomic Medicine
Volume5
Issue number1
DOIs
Publication statusPublished - Dec 2020

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