Title | Towards accurate and reliable resolution of structural variants for clinical diagnosis. |
Publication Type | Journal Article |
Year of Publication | 2022 |
Authors | Liu, Z, Roberts, R, Mercer, TR, Xu, J, Sedlazeck, FJ, Tong, W |
Journal | Genome Biol |
Volume | 23 |
Issue | 1 |
Pagination | 68 |
Date Published | 2022 Mar 03 |
ISSN | 1474-760X |
Keywords | Genomic Structural Variation, Phenotype, Reproducibility of Results |
Abstract | Structural variants (SVs) are a major source of human genetic diversity and have been associated with different diseases and phenotypes. The detection of SVs is difficult, and a diverse range of detection methods and data analysis protocols has been developed. This difficulty and diversity make the detection of SVs for clinical applications challenging and requires a framework to ensure accuracy and reproducibility. Here, we discuss current developments in the diagnosis of SVs and propose a roadmap for the accurate and reproducible detection of SVs that includes case studies provided from the FDA-led SEquencing Quality Control Phase II (SEQC-II) and other consortium efforts. |
DOI | 10.1186/s13059-022-02636-8 |
Alternate Journal | Genome Biol |
PubMed ID | 35241127 |
PubMed Central ID | PMC8892125 |
Grant List | U01 HG011758 / HG / NHGRI NIH HHS / United States UM1 HG008898 / HG / NHGRI NIH HHS / United States |
Towards accurate and reliable resolution of structural variants for clinical diagnosis.
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