| Literature DB >> 28188908 |
Vahan Simonyan1, Konstantin Chumakov2, Eric Donaldson3, Konstantinos Karagiannis4, Phuc VinhNguyen Lam5, Hayley Dingerdissen6, Alin Voskanian7.
Abstract
Advances in high-throughput sequencing (HTS) technologies have greatly increased the availability of genomic data and potential discovery of clinically significant genomic variants. However, numerous issues still exist with the analysis of these data, including data complexity, the absence of formally agreed upon best practices, and inconsistent reproducibility. Toward a more robust and reproducible variant-calling paradigm, we propose a series of selective noise filtrations and post-alignment quality control (QC) techniques that may reduce the rate of false variant calls. We have implemented both novel and refined post-alignment QC mechanisms to augment existing pre-alignment QC measures. These techniques can be used independently or in combination to identify and correct issues caused during data generation or early analysis stages. The adoption of these procedures by the broader scientific community is expected to improve the identification of clinically significant variants both in terms of computational efficiency and in the confidence of the results. AVAILABILITY: https://hive.biochemistry.gwu.edu/.Entities:
Keywords: Genome assembly; HTS; NGS; Post-alignment quality control; SNP; Variant-calling
Mesh:
Year: 2017 PMID: 28188908 DOI: 10.1016/j.ygeno.2017.01.002
Source DB: PubMed Journal: Genomics ISSN: 0888-7543 Impact factor: 5.736