Toward highly accurate and fast variant and de novo mutation identification from high-throughput sequencing data by joint Bayesian family calling

Francisco M. De La Vega, Mehul Rathod, Richard Littin, Len Trigg, John G. Cleary


Our results suggest that joint family calling produces more accurate calls than singleton calling and allows for the assessment of de novo mutation candidates with much less noise. We illustrate the impact of an improved call set in the downstream interpretation analysis of a simulated cased from the literature, and a real case from a cardio-pulmonary syndrome. We believe the analytical advances we present are crucial for the clinical adoption of genome and exome sequence data in family disease studies and beyond.

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