- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
1 Online-Ressource.
- Language
-
Englisch
- Bibliographic citation
-
Comprehensive benchmarking and guidelines of mosaic variant calling strategies ; volume:20 ; number:12 ; day:12 ; month:10 ; year:2023 ; pages:2058-2067 ; date:12.2023
Nature methods ; 20, Heft 12 (12.10.2023), 2058-2067, 12.2023
- Creator
-
Ha, Yoo-Jin
Kang, Seungseok
Kim, Jisoo
Kim, Junhan
Jo, Se-Young
Kim, Sangwoo
- Contributor
-
SpringerLink (Online service)
- DOI
-
10.1038/s41592-023-02043-2
- URN
-
urn:nbn:de:101:1-2024022308093181081468
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
14.08.2025, 10:54 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Ha, Yoo-Jin
- Kang, Seungseok
- Kim, Jisoo
- Kim, Junhan
- Jo, Se-Young
- Kim, Sangwoo
- SpringerLink (Online service)
Other Objects (12)
Benchmarking datasets for assembly-based variant calling using high-fidelity long reads
Integrated approach to generate artificial samples with low tumor fraction for somatic variant calling benchmarking
Benchmarking workflows to assess performance and suitability of germline variant calling pipelines in clinical diagnostic assays
BBCAnalyzer: a visual approach to facilitate variant calling
CoVaCS: a consensus variant calling system
Best practices for variant calling in clinical sequencing
Structural variant calling using third-generation sequencing data
Essential guidelines for computational method benchmarking
Alternate-locus aware variant calling in whole genome sequencing
Improving variant calling using population data and deep learning
satmut_utils: a simulation and variant calling package for multiplexed assays of variant effect
Understanding the Basics of NGS: From Mechanism to Variant Calling
Benchmarking datasets for assembly-based variant calling using high-fidelity long reads
Integrated approach to generate artificial samples with low tumor fraction for somatic variant calling benchmarking
Benchmarking workflows to assess performance and suitability of germline variant calling pipelines in clinical diagnostic assays
BBCAnalyzer: a visual approach to facilitate variant calling
CoVaCS: a consensus variant calling system
Best practices for variant calling in clinical sequencing
Structural variant calling using third-generation sequencing data
Essential guidelines for computational method benchmarking
Alternate-locus aware variant calling in whole genome sequencing
Improving variant calling using population data and deep learning
satmut_utils: a simulation and variant calling package for multiplexed assays of variant effect
Understanding the Basics of NGS: From Mechanism to Variant Calling
Benchmarking datasets for assembly-based variant calling using high-fidelity long reads
Integrated approach to generate artificial samples with low tumor fraction for somatic variant calling benchmarking
Benchmarking workflows to assess performance and suitability of germline variant calling pipelines in clinical diagnostic assays
BBCAnalyzer: a visual approach to facilitate variant calling
CoVaCS: a consensus variant calling system
Best practices for variant calling in clinical sequencing
Structural variant calling using third-generation sequencing data
Essential guidelines for computational method benchmarking
Alternate-locus aware variant calling in whole genome sequencing
Improving variant calling using population data and deep learning
satmut_utils: a simulation and variant calling package for multiplexed assays of variant effect