Benchmarking of computational error-correction methods for next-generation sequencing data

BACKGROUND: Recent advancements in next-generation sequencing have rapidly improved our ability to study genomic material at an unprecedented scale. Despite substantial improvements in sequencing technologies, errors present in the data still risk confounding downstream analysis and limiting the app...

Descripción completa

Detalles Bibliográficos
Autores principales: Mitchell, Keith, Brito, Jaqueline J., Mandric, Igor, Wu, Qiaozhen, Knyazev, Sergey, Chang, Sei, Martin, Lana S., Karlsberg, Aaron, Gerasimov, Ekaterina, Littman, Russell, Hill, Brian L., Wu, Nicholas C., Yang, Harry Taegyun, Hsieh, Kevin, Chen, Linus, Littman, Eli, Shabani, Taylor, Enik, German, Yao, Douglas, Sun, Ren, Schroeder, Jan, Eskin, Eleazar, Zelikovsky, Alex, Skums, Pavel, Pop, Mihai, Mangul, Serghei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7079412/
https://www.ncbi.nlm.nih.gov/pubmed/32183840
http://dx.doi.org/10.1186/s13059-020-01988-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7079412/
https://www.ncbi.nlm.nih.gov/pubmed/32183840
http://dx.doi.org/10.1186/s13059-020-01988-3

Ejemplares similares