Journal Article

Opportunities and challenges in long-read sequencing data analysis

Amarasinghe, Shanika L., Su, Shian, Dong, Xueyi, Zappia, Luke, Ritchie, Matthew E., Gouil, Quentin

2020

Overview

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.

• Publisher: BioMed Central,Springer Nature B.V,BMC
• Subject: Accuracy / Animal Genetics and Genomics / Animals / Bioinformatics / Biomedical and Life Sciences / Data analysis / Data Science - methods / Data Science - standards / Deoxyribonucleic acid / DNA / DNA methylation / Error correction & detection / Evolutionary Biology / genome / genomics / Genomics - methods / Genomics - standards / Human Genetics / Humans / landscapes / Life Sciences / Long-read sequencing / Microbial Genetics and Genomics / Nanopore Sequencing - methods / Nanopore Sequencing - standards / Neural networks / Oxford Nanopore / PacBio / Plant Genetics and Genomics / Remakes & sequels / Review / Reviews / transcriptomics / Whole Genome Sequencing - methods / Whole Genome Sequencing - standards