Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation.

Published online

Journal Article

Advancements in the cost and speed of next generation genetic sequencing have generated an explosion of clinical whole exome and whole genome testing. While this has led to increased identification of likely pathogenic mutations associated with genetic syndromes, it has also dramatically increased the number of incidentally found genetic variants of unknown significance (VUS). Determining the clinical significance of these variants is a major challenge for both scientists and clinicians. An approach to assist in determining the likelihood of pathogenicity is signal-to-noise analysis at the protein sequence level. This protocol describes a method for amino acid-level signal-to-noise analysis that leverages variant frequency at each amino acid position of the protein with known protein topology to identify areas of the primary sequence with elevated likelihood of pathologic variation (relative to population "background" variation). This method can identify amino acid residue location "hotspots" of high pathologic signal, which can be used to refine the diagnostic weight of VUSs such as those identified by next generation genetic testing.

Full Text

Duke Authors

Cited Authors

  • Jones, EG; Landstrom, AP

Published Date

  • January 16, 2019

Published In

PubMed ID

  • 30735170

Pubmed Central ID

  • 30735170

Electronic International Standard Serial Number (EISSN)

  • 1940-087X

Digital Object Identifier (DOI)

  • 10.3791/58907

Language

  • eng

Conference Location

  • United States