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Opportunities and challenges in long-read sequencing data analysis

Long-read technologies are overcoming early limitations in accuracy and throughput, broadening their application domains in genomics. Dedicated analysis tools that take into account the characteristics of long-read data are thus required, but the fast pace of development of such tools can be overwhe...

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Detalles Bibliográficos
Autores principales: Amarasinghe, Shanika L., Su, Shian, Dong, Xueyi, Zappia, Luke, Ritchie, Matthew E., Gouil, Quentin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7006217/
https://www.ncbi.nlm.nih.gov/pubmed/32033565
http://dx.doi.org/10.1186/s13059-020-1935-5
Descripción
Sumario:Long-read technologies are overcoming early limitations in accuracy and throughput, broadening their application domains in genomics. Dedicated analysis tools that take into account the characteristics of long-read data are thus required, but the fast pace of development of such tools can be overwhelming. To assist in the design and analysis of long-read sequencing projects, we review the current landscape of available tools and present an online interactive database, long-read-tools.org, to facilitate their browsing. We further focus on the principles of error correction, base modification detection, and long-read transcriptomics analysis and highlight the challenges that remain.