FVC as an adaptive and accurate method for filtering variants from popular NGS analysis pipelines
FVC is a method for calling specific gene variants from whole genome data, for potential use in clinical diagnosis and human genetics research.
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2022-09-01
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| Series: | Communications Biology |
| Online Access: | https://doi.org/10.1038/s42003-022-03397-7 |
| _version_ | 1811267709103505408 |
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| author | Yongyong Ren Yan Kong Xiaocheng Zhou Georgi Z. Genchev Chao Zhou Hongyu Zhao Hui Lu |
| author_facet | Yongyong Ren Yan Kong Xiaocheng Zhou Georgi Z. Genchev Chao Zhou Hongyu Zhao Hui Lu |
| author_sort | Yongyong Ren |
| collection | DOAJ |
| description | FVC is a method for calling specific gene variants from whole genome data, for potential use in clinical diagnosis and human genetics research. |
| first_indexed | 2024-04-12T21:07:44Z |
| format | Article |
| id | doaj.art-d2b56127d864494b8c4403baffe691d7 |
| institution | Directory Open Access Journal |
| issn | 2399-3642 |
| language | English |
| last_indexed | 2024-04-12T21:07:44Z |
| publishDate | 2022-09-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Communications Biology |
| spelling | doaj.art-d2b56127d864494b8c4403baffe691d72022-12-22T03:16:40ZengNature PortfolioCommunications Biology2399-36422022-09-01511910.1038/s42003-022-03397-7FVC as an adaptive and accurate method for filtering variants from popular NGS analysis pipelinesYongyong Ren0Yan Kong1Xiaocheng Zhou2Georgi Z. Genchev3Chao Zhou4Hongyu Zhao5Hui Lu6State Key Laboratory of Microbial metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong UniversityState Key Laboratory of Microbial metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong UniversityState Key Laboratory of Microbial metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong UniversityResearch Affairs, Faculty of Medicine, Chulalongkorn UniversityState Key Laboratory of Microbial metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong UniversityDepartment of Biostatistics, Yale UniversityState Key Laboratory of Microbial metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong UniversityFVC is a method for calling specific gene variants from whole genome data, for potential use in clinical diagnosis and human genetics research.https://doi.org/10.1038/s42003-022-03397-7 |
| spellingShingle | Yongyong Ren Yan Kong Xiaocheng Zhou Georgi Z. Genchev Chao Zhou Hongyu Zhao Hui Lu FVC as an adaptive and accurate method for filtering variants from popular NGS analysis pipelines Communications Biology |
| title | FVC as an adaptive and accurate method for filtering variants from popular NGS analysis pipelines |
| title_full | FVC as an adaptive and accurate method for filtering variants from popular NGS analysis pipelines |
| title_fullStr | FVC as an adaptive and accurate method for filtering variants from popular NGS analysis pipelines |
| title_full_unstemmed | FVC as an adaptive and accurate method for filtering variants from popular NGS analysis pipelines |
| title_short | FVC as an adaptive and accurate method for filtering variants from popular NGS analysis pipelines |
| title_sort | fvc as an adaptive and accurate method for filtering variants from popular ngs analysis pipelines |
| url | https://doi.org/10.1038/s42003-022-03397-7 |
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