Opportunities and challenges in long-read sequencing data analysis
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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.
Citation
@article{l_amarasinghe2020,
author = {L Amarasinghe, Shanika and Su, Shian and Dong, Xueyi and
Zappia, Luke and E Ritchie, Matthew and Gouil, Quentin},
title = {Opportunities and Challenges in Long-Read Sequencing Data
Analysis},
journal = {Genome biology},
volume = {21},
number = {1},
pages = {30},
date = {2020-02-01},
url = {https://doi.org/10.1186/s13059-020-1935-5},
doi = {10.1186/s13059-020-1935-5},
issn = {1465-6906},
langid = {en},
abstract = {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.}
}