LRScaf: Improving Draft Genomes Using Long Noisy Reads

Abstract

LRScaf is faster 300 times for S. cerevisiae and 2,300 times for D. melanogaster. The peak 38 RAM of LRScaf, by contrast, is more efficient than LINKS in our test. For the rice case, the peak RAM of LINKS (877.72 Gb) is about 196 times higher than LRScaf. For the experiment 40 of human assembly, the peak RAM of LINKS is beyond the capacity of system memory (1 Tb) whereas LRScaf takes 20. 28 and 41.20 Gb on CHM1 and NA12878 datasets. 42 With the advent of Next Generation Sequencing (NGS) technologies, the genomics community 50 has made significant contributions to de novo assembling genomes. Despite that many studies and tools are aimed at reconstructing NGS data into complete de novo assemblies of genomes, 52 this goal is difficult to achieve because of intrinsic limitation of NGS data, i.e., read lengths are shorter than most of the repetitive sequences [1]. The existence of repeats makes it difficult to 54 reconstruct complete genomes instead of generating a large set of contiguous sequences (contigs) even when the sequencing coverage is high [2]. Thus, attention is focused on the 56 so-called genomic scaffolding procedure, which aims at reducing the number of contigs by using fragments of moderate lengths whose ends are sequenced (double-barreled data) [3,4]. 58Nevertheless, major genomic regions still hinder genomic assemblies because of, primarily, large-size repeat and low coverage. In response, Third Generation Sequencing (TGS) 60 technologies have been developed. TGS sheds light on different alternatives to solve genome assembly problems by offering very long reads, e.g., the Single Molecule Real Time (SMRT) 62delivers read lengths of up to 50 Kb [5] and the nanopore sequencing technology of Oxford Nanopore Technologies ® (ONT) delivers 64 read lengths which are greater than 800 Kb [6]. These long reads suffer from high sequencing error rates, however, which necessitates high coverage during the genome assembly [7]. In 66 4 addition, TGS technologies have a higher cost per base than NGS methods. Consequently, long reads are more commonly used for scaffolding draft assemblies generated from NGS data than 68 for de novo assembly [8].The process of genome assembly is typically divided into two major steps. The first step is to 70 piece overlapping reads together into contigs which is commonly done using the de Bruijn or overlap graph [1]. The second step is to assemble scaffolds, consisting of ordered sequences of 72 oriented contigs with estimated distances between them. Scaffolding, which was first introduced by Huson [3], is a critical part of the genome assembly process, especially for NGS 74data. Yet, scaffolding is a research area that remains largely open because of the NP-hard complexity [9]. By using paired-end and/or mate-pair reads linking information, a number of 76 standalone scaffolders, e.g. Bambus [4], MIP [10], Opera [11], SCARPA [12], SOPRA [13], SSPACE [14], BESST [15], and BOSS [16], have been developed. Nevertheless, a recent 78comprehensive evaluation showed that scaffolding was stil...

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In vivo augmentation of a complex gut bacterial community

“…Hybrid assembly was performed by Unicycler v. 0.4.8 (Wick et al 2017) with default parameters using preprocessed reads. After assembly, the contigs from the assembler were scaffolded by LRScaf v. 1.1.9 (Qin et al 2018) with default parameters. If the initial assembly did not produce the complete genome, gaps were filled using long reads by TGS-GapCloser v. 1.0.1 (Xu et al 2019) with default parameters.…”