Cargando…
Estimating sequencing error rates using families
BACKGROUND: As next-generation sequencing technologies make their way into the clinic, knowledge of their error rates is essential if they are to be used to guide patient care. However, sequencing platforms and variant-calling pipelines are continuously evolving, making it difficult to accurately qu...
Autores principales: | Paskov, Kelley, Jung, Jae-Yoon, Chrisman, Brianna, Stockham, Nate T., Washington, Peter, Varma, Maya, Sun, Min Woo, Wall, Dennis P. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8063364/ https://www.ncbi.nlm.nih.gov/pubmed/33892748 http://dx.doi.org/10.1186/s13040-021-00259-6 |
Ejemplares similares
-
The human “contaminome”: bacterial, viral, and computational contamination in whole genome sequences from 1000 families
por: Chrisman, Brianna, et al.
Publicado: (2022) -
Transmission dynamics of human herpesvirus 6A, 6B and 7 from whole genome sequences of families
por: Chrisman, Brianna S., et al.
Publicado: (2022) -
Localizing unmapped sequences with families to validate the Telomere-to-Telomere assembly and identify new hotspots for genetic diversity
por: Chrisman, Brianna, et al.
Publicado: (2023) -
A maximum flow-based network approach for identification of stable noncoding biomarkers associated with the multigenic neurological condition, autism
por: Varma, Maya, et al.
Publicado: (2021) -
Outgroup Machine Learning Approach Identifies Single Nucleotide Variants in Noncoding DNA Associated with Autism Spectrum Disorder
por: Varma, Maya, et al.
Publicado: (2019)