BackgroundThe advent of third-generation sequencing (TGS) technologies opens the door to improve genome assembly. Long reads are promising for enhancing the quality of fragmented draft assemblies constructed from next-generation sequencing (NGS) technologies. To date, a few algorithms that are capable of improving draft assemblies have released. There are SSPACE-LongRead, OPERA-LG, SMIS, npScarf, DBG2OLC, Unicycler, and LINKS. Hybrid assembly on large genomes remains challenging, however.ResultsWe develop a scalable and computationally efficient scaffolder, Long Reads Scaffolder (LRScaf, https://github.com/shingocat/lrscaf), that is capable of significantly boosting assembly contiguity using long reads. In this study, we summarise a comprehensive performance assessment for state-of-the-art scaffolders and LRScaf on seven organisms, i.e., E. coli, S. cerevisiae, A. thaliana, O. sativa, S. pennellii, Z. mays, and H. sapiens. LRScaf significantly improves the contiguity of draft assemblies, e.g., increasing the NGA50 value of CHM1 from 127.1 kbp to 9.4 Mbp using 20-fold coverage PacBio dataset and the NGA50 value of NA12878 from 115.3 kbp to 12.9 Mbp using 35-fold coverage Nanopore dataset. Besides, LRScaf generates the best contiguous NGA50 on A. thaliana, S. pennellii, Z. mays, and H. sapiens. Moreover, LRScaf has the shortest run time compared with other scaffolders, and the peak RAM of LRScaf remains practical for large genomes (e.g., 20.3 and 62.6 GB on CHM1 and NA12878, respectively).ConclusionsThe new algorithm, LRScaf, yields the best or, at least, moderate scaffold contiguity and accuracy in the shortest run time compared with other scaffolding algorithms. Furthermore, LRScaf provides a cost-effective way to improve contiguity of draft assemblies on large genomes.

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...

Objectives The rapid development of cerebral organoid technology and the gradual maturity of cerebral organoids highlight the necessity of foresighted research on relevant ethical concerns. We employed knowledge graphs and conducted statistical analysis with CiteSpace for a comprehensive analysis of the status quo of the research on the ethical concerns of cerebral organoids from a bibliometric perspective. Materials and Methods We performed a statistical analysis of published papers on cerebral organoid ethics, keyword co‐occurrence graph, literature co‐citation and knowledge clustering graph to examine the status of the ethics research, internal relationship between technological development and ethical research, and ethical concerns of the academia. Finally, we used a keyword time zone graph and related statistics to analyze and predict the trends and popular topics of future cerebral organoids ethics research. Results We demonstrated that although the ethical concerns of cerebral organoids have long been discussed, it was not until 2017 that the ethical issues began to receive more attention, when cerebral organoids were gradually mimicking the human brain more closely and increasingly being combined with chimera research. The recent key ethical concerns are primarily divided into three categories: concerns that are common in life sciences, specific to cerebral organoids, and present in cross‐fields. These increasing ethical concerns are inherently related to the continual development of technology. The analysis pointed out that future research should focus on the ethical concerns of consciousness that are unique to cerebral organoids, ethical concerns of cross‐fields, and construction and improvement of legislative and regulatory systems. Conclusions Although research on cerebral organoids can benefit the biomedicine field, the relevant ethical concerns are significant and have received increasing attention, which are inherently related to the continual development of technology. Future studies in ethics regarding cerebral organoid research should focus on the ethical concerns of consciousness, and cross‐fields, as well as the improvement of regulatory systems.