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Updated: Apr 30, 2026

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
Published on: April 4, 2018
Using VAAST to Identify Disease-Associated Variants in Next-Generation Sequencing Data.
Brett Kennedy1,2, Zev Kronenberg1,2, Hao Hu3,2
1Department of Human Genetics, University of Utah School of Medicine, Salt Lake City, Utah.
This study details best practices for variant prioritization using the VAAST pipeline for next-generation sequencing data. It covers case-control, small pedigree, and large pedigree analyses for identifying disease-associated alleles.
Area of Science:
- Genomics
- Bioinformatics
Background:
- Next-generation sequencing (NGS) generates vast amounts of data.
- Identifying disease-associated genetic variants is crucial for genetic research and diagnostics.
Purpose of the Study:
- To provide protocols for variant prioritization using the VAAST pipeline.
- To guide users on best practices for analyzing NGS data for disease-associated alleles.
Main Methods:
- Utilizing the VAAST pipeline for variant analysis.
- Applying VAAST, VAAST 2.0, and pVAAST for genetic data interpretation.
- Demonstrating protocols with provided examples and test data.
Main Results:
- Established best practices for variant prioritization in various genetic analysis scenarios.
- Provided comprehensive protocols for VAAST, VAAST 2.0, and pVAAST.
- Facilitated understanding of disease-associated allele identification in different pedigree structures.
Conclusions:
- The VAAST pipeline offers a robust framework for identifying disease-associated alleles.
- These protocols enhance the utility of VAAST for researchers analyzing complex genetic data.
- Effective variant prioritization is key to advancing genetic disease research.
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