Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation.
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.
Duke Scholars
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Related Subject Headings
- Signal-To-Noise Ratio
- Proteins
- Mutation
- Likelihood Functions
- KCNQ1 Potassium Channel
- Humans
- Genetic Variation
- Gene Frequency
- Amino Acids
- 3101 Biochemistry and cell biology
Citation
Published In
DOI
EISSN
Publication Date
Issue
Location
Related Subject Headings
- Signal-To-Noise Ratio
- Proteins
- Mutation
- Likelihood Functions
- KCNQ1 Potassium Channel
- Humans
- Genetic Variation
- Gene Frequency
- Amino Acids
- 3101 Biochemistry and cell biology