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Current challenges and solutions of de novoassembly

Authors :
Liao, Xingyu
Li, Min
Zou, You
Wu, Fang-Xiang
Yi-Pan
Wang, Jianxin
Source :
Quantitative Biology; June 2019, Vol. 7 Issue: 2 p90-109, 20p
Publication Year :
2019

Abstract

Next-generation sequencing (NGS) technologies have fostered an unprecedented proliferation of high-throughput sequencing projects and a concomitant development of novel algorithms for the assembly of short reads. However, numerous technical or computational challenges in de novoassembly still remain, although many new ideas and solutions have been suggested to tackle the challenges in both experimental and computational settings. In this review, we first briefly introduce some of the major challenges faced by NGS sequence assembly. Then, we analyze the characteristics of various sequencing platforms and their impact on assembly results. After that, we classify de novoassemblers according to their frameworks (overlap graph-based, de Bruijngraph-based and string graph-based), and introduce the characteristics of each assembly tool and their adaptation scene. Next, we introduce in detail the solutions to the main challenges of de novoassembly of next generation sequencing data, single-cell sequencing data and single molecule sequencing data. At last, we discuss the application of SMS long reads in solving problems encountered in NGS assembly. This review not only gives an overview of the latest methods and developments in assembly algorithms, but also provides guidelines to determine the optimal assembly algorithm for a given input sequencing data type.

Details

Language :
English
ISSN :
20954689 and 20954697
Volume :
7
Issue :
2
Database :
Supplemental Index
Journal :
Quantitative Biology
Publication Type :
Periodical
Accession number :
ejs49893767
Full Text :
https://doi.org/10.1007/s40484-019-0166-9