دورية أكاديمية
SV2: accurate structural variation genotyping and de novo mutation detection from whole genomes.
| العنوان: | SV2: accurate structural variation genotyping and de novo mutation detection from whole genomes. |
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| المؤلفون: | Antaki D; Beyster Center for Genomics of Psychiatric Diseases.; Department of Psychiatry.; Department of Cellular and Molecular Medicine and Pediatrics.; Biomedical Sciences Graduate Program, University of California San Diego, La Jolla, CA 92093, USA., Brandler WM; Beyster Center for Genomics of Psychiatric Diseases.; Department of Psychiatry.; Department of Cellular and Molecular Medicine and Pediatrics., Sebat J; Beyster Center for Genomics of Psychiatric Diseases.; Department of Psychiatry.; Department of Cellular and Molecular Medicine and Pediatrics. |
| المصدر: | Bioinformatics (Oxford, England) [Bioinformatics] 2018 May 15; Vol. 34 (10), pp. 1774-1777. |
| نوع المنشور: | Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't |
| اللغة: | English |
| بيانات الدورية: | Publisher: Oxford University Press Country of Publication: England NLM ID: 9808944 Publication Model: Print Cited Medium: Internet ISSN: 1367-4811 (Electronic) Linking ISSN: 13674803 NLM ISO Abbreviation: Bioinformatics Subsets: MEDLINE |
| أسماء مطبوعة: | Original Publication: Oxford : Oxford University Press, c1998- |
| مواضيع طبية MeSH: | Genome, Human* , Mutation*, Algorithms ; Genotype ; High-Throughput Nucleotide Sequencing ; Humans ; Sequence Analysis, DNA ; Software ; Whole Genome Sequencing |
| مستخلص: | Motivation: Structural variation (SV) detection from short-read whole genome sequencing is error prone, presenting significant challenges for population or family-based studies of disease. Results: Here, we describe SV2, a machine-learning algorithm for genotyping deletions and duplications from paired-end sequencing data. SV2 can rapidly integrate variant calls from multiple structural variant discovery algorithms into a unified call set with high genotyping accuracy and capability to detect de novo mutations. Availability and Implementation: SV2 is freely available on GitHub (https://github.com/dantaki/SV2). Contact: jsebat@ucsd.edu. Supplementary Information: Supplementary data are available at Bioinformatics online. |
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| معلومات مُعتمدة: | R01 MH076431 United States MH NIMH NIH HHS; R01 MH113715 United States MH NIMH NIH HHS; T32 GM008666 United States GM NIGMS NIH HHS; U41 HG007497 United States HG NHGRI NIH HHS |
| تواريخ الأحداث: | Date Created: 20180105 Date Completed: 20190717 Latest Revision: 20190717 |
| رمز التحديث: | 20221213 |
| مُعرف محوري في PubMed: | PMC5946924 |
| DOI: | 10.1093/bioinformatics/btx813 |
| PMID: | 29300834 |
| قاعدة البيانات: | MEDLINE |
| تدمد: | 1367-4811 |
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| DOI: | 10.1093/bioinformatics/btx813 |