Barcode-free next-generation sequencing error validation for ultra-rare variant detection
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
-
2041-1723
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Anmerkungen
-
online resource.
- Erschienen in
-
Barcode-free next-generation sequencing error validation for ultra-rare variant detection ; volume:10 ; number:1 ; day:28 ; month:2 ; year:2019 ; pages:1-8 ; date:12.2019
Nature Communications ; 10, Heft 1 (28.2.2019), 1-8, 12.2019
- Urheber
-
Yeom, Huiran
Lee, Yonghee
Ryu, Taehoon
Noh, Jinsung
Lee, Amos Chungwon
Lee, Han-Byoel
Kang, Eunji
Song, Seo Woo
Kwon, Sunghoon
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
-
10.1038/s41467-019-08941-4
- URN
-
urn:nbn:de:101:1-2019032023050099560862
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
14.08.2025, 10:53 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Yeom, Huiran
- Lee, Yonghee
- Ryu, Taehoon
- Noh, Jinsung
- Lee, Amos Chungwon
- Lee, Han-Byoel
- Kang, Eunji
- Song, Seo Woo
- Kwon, Sunghoon
- SpringerLink (Online service)
Ähnliche Objekte (12)
Next-generation sequencing algorithms : from read mapping to variant detection
Next-generation sequencing algorithms : from read mapping to variant detection
Analysis of error profiles in deep next-generation sequencing data
Effects of error-correction of heterozygous next-generation sequencing data
Efficient error correction for next-generation sequencing of viral amplicons
Empirical Bayes single nucleotide variant-calling for next-generation sequencing data
Evaluating Variant Calling Tools for Non-Matched Next-Generation Sequencing Data
Validation and assessment of variant calling pipelines for next-generation sequencing
Benchmarking of computational error-correction methods for next-generation sequencing data
An integrative variant analysis suite for whole exome next-generation sequencing data
GemSIM: general, error-model based simulator of next-generation sequencing data
Next-Generation Macrolide Antibiotics
Next-generation sequencing algorithms : from read mapping to variant detection
Next-generation sequencing algorithms : from read mapping to variant detection
Analysis of error profiles in deep next-generation sequencing data
Effects of error-correction of heterozygous next-generation sequencing data
Efficient error correction for next-generation sequencing of viral amplicons
Empirical Bayes single nucleotide variant-calling for next-generation sequencing data
Evaluating Variant Calling Tools for Non-Matched Next-Generation Sequencing Data
Validation and assessment of variant calling pipelines for next-generation sequencing
Benchmarking of computational error-correction methods for next-generation sequencing data
An integrative variant analysis suite for whole exome next-generation sequencing data
GemSIM: general, error-model based simulator of next-generation sequencing data
Next-Generation Macrolide Antibiotics
Next-generation sequencing algorithms : from read mapping to variant detection
Next-generation sequencing algorithms : from read mapping to variant detection
Analysis of error profiles in deep next-generation sequencing data
Effects of error-correction of heterozygous next-generation sequencing data
Efficient error correction for next-generation sequencing of viral amplicons
Empirical Bayes single nucleotide variant-calling for next-generation sequencing data
Evaluating Variant Calling Tools for Non-Matched Next-Generation Sequencing Data
Validation and assessment of variant calling pipelines for next-generation sequencing
Benchmarking of computational error-correction methods for next-generation sequencing data
An integrative variant analysis suite for whole exome next-generation sequencing data
GemSIM: general, error-model based simulator of next-generation sequencing data