Empirical evaluation of methods for de novo genome assembly

Y Technologies for next-generation sequencing (NGS) have stimulated an exponential rise in high-throughput sequencing projects and resulted in the development of new read-assembly algorithms. A drastic reduction in the costs of generating short reads on the genomes of new organisms is attributable to recent advances in NGS technologies such as Ion Torrent, Illumina, and PacBio. Genome research has led to the creation of high-quality reference genomes for several organisms, and de novo assembly is a key initiative that has facilitated gene discovery and other studies. More powerful analytical algorithms are needed to work on the increasing amount of sequence data. We make a thorough comparison of the de novo assembly algorithms to allow new users to clearly understand the assembly algorithms: overlap-layout-consensus and de-Bruijn-graph, string-graph based assembly, and hybrid approach. We also address the computational efficacy of each algorithm's performance, challenges faced by the assembly tools used, and the impact of repeats. Our results compare the relative performance of the different assemblers and other related assembly differences with and without the reference genome. We hope that this analysis will contribute to further the application of de novo sequences and help the future growth of assembly algorithms.

Automated summary

This article explores the rapid growth of high-throughput sequencing projects and new read-assembly algorithms driven by next-generation sequencing technologies like Ion Torrent, Illumina, and PacBio. Genome research has led to the creation of high-quality reference genomes for various organisms, with de novo assembly playing a crucial role in gene discovery and other studies. The article provides a thorough comparison of different assembly algorithms to aid new users in understanding them better.