genome scaffolding
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Algorithmica ◽  
2021 ◽  
Author(s):  
Tom Davot ◽  
Annie Chateau ◽  
Rodolphe Giroudeau ◽  
Mathias Weller ◽  
Dorine Tabary

2021 ◽  
Author(s):  
Tom Davot ◽  
Annie Chateau ◽  
Rohan Fossé ◽  
Rodolphe Giroudeau ◽  
Mathias Weller

Abstract Background: Scaffolding is a bioinformatics problem aimed at completing the contig assembly process by determining the relative position and orientation of these contigs. It can be seen as a paths and cycles cover problem of a particular graph called the “scaffold graph”.Results: We provide some NP-hardness and inapproximability results on this problem. We also adapt a greedy approximation algorithm on complete graphs so that it works on a special class aiming to be close to real instances. The described algorithm is the first polynomial-time approximation algorithm designed for this problem on non-complete graphs.Conclusion: Tests on a set of simulated instances show that our algorithm provides better results than the version on complete graphs.


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Mitsutaka Kadota ◽  
Kazuaki Yamaguchi ◽  
Yuichiro Hara ◽  
Shigehiro Kuraku
Keyword(s):  

2020 ◽  
Vol 27 (4) ◽  
pp. 519-533 ◽  
Author(s):  
Weihua Pan ◽  
Tao Jiang ◽  
Stefano Lonardi

GigaScience ◽  
2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Mitsutaka Kadota ◽  
Osamu Nishimura ◽  
Hisashi Miura ◽  
Kaori Tanaka ◽  
Ichiro Hiratani ◽  
...  

Abstract Background Hi-C is derived from chromosome conformation capture (3C) and targets chromatin contacts on a genomic scale. This method has also been used frequently in scaffolding nucleotide sequences obtained by de novo genome sequencing and assembly, in which the number of resultant sequences rarely converges to the chromosome number. Despite its prevalent use, the sample preparation methods for Hi-C have not been intensively discussed, especially from the standpoint of genome scaffolding. Results To gain insight into the best practice of Hi-C scaffolding, we performed a multifaceted methodological comparison using vertebrate samples and optimized various factors during sample preparation, sequencing, and computation. As a result, we identified several key factors that helped improve Hi-C scaffolding, including the choice and preparation of tissues, library preparation conditions, the choice of restriction enzyme(s), and the choice of scaffolding program and its usage. Conclusions This study provides the first comparison of multiple sample preparation kits/protocols and computational programs for Hi-C scaffolding by an academic third party. We introduce a customized protocol designated “inexpensive and controllable Hi-C (iconHi-C) protocol,” which incorporates the optimal conditions identified in this study, and demonstrate this technique on chromosome-scale genome sequences of the Chinese softshell turtle Pelodiscus sinensis.


2019 ◽  
Author(s):  
Mitsutaka Kadota ◽  
Osamu Nishimura ◽  
Hisashi Miura ◽  
Kaori Tanaka ◽  
Ichiro Hiratani ◽  
...  

AbstractBackgroundHi-C, a derivative of chromosome conformation capture (3C) targeting the whole genome, was originally developed as a means for characterizing chromatin conformation. More recently, this method has also been frequently employed in elongating nucleotide sequences obtained by de novo genome sequencing and assembly, in which the number of resultant sequences rarely converge into the chromosome number. Despite the prevailing and irreplaceable use, sample preparation methods for Hi-C have not been intensively discussed, especially from the standpoint of genome scaffolding.ResultsTo gain insights into the best practice of Hi-C scaffolding, we performed a multifaceted methodological comparison using vertebrate samples and optimized various factors during sample preparation, sequencing, and computation. As a result, we have identified some key factors that help improve Hi-C scaffolding including the choice and preparation of tissues, library preparation conditions, and restriction enzyme(s), as well as the choice of scaffolding program and its usage.ConclusionsThis study provides the first comparison of multiple sample preparation kits/protocols and computational programs for Hi-C scaffolding, by an academic third party. We introduce a customized protocol designated the ‘inexpensive and controllable Hi-C (iconHi-C) protocol’, in which the optimal conditions revealed by this study have been incorporated, and release the resultant chromosome-scale genome assembly of the Chinese softshell turtle Pelodiscus sinensis.


2019 ◽  
Author(s):  
Weihua Pan ◽  
Tao Jiang ◽  
Stefano Lonardi

AbstractDue to the current limitations of sequencing technologies,de novogenome assembly is typically carried out in two stages, namely contig (sequence) assembly and scaffolding. While scaffolding is computationally easier than sequence assembly, the scaffolding problem can be challenging due to the high repetitive content of eukaryotic genomes, possible mis-joins in assembled contigs and inaccuracies in the linkage information. Genome scaffolding tools either use paired-end/mate-pair/linked/Hi-C reads or genome-wide maps (optical, physical or genetic) as linkage information. Optical maps (in particular Bionano Genomics maps) have been extensively used in many recent large-scale genome assembly projects (e.g., goat, apple, barley, maize, quinoa, sea bass, among others). However, the most commonly used scaffolding tools have a serious limitation: they can only deal with one optical map at a time, forcing users to alternate or iterate over multiple maps. In this paper, we introduce a novel scaffolding algorithm called OMGS that for the first time can take advantages of multiple optical maps. OMGS solves several optimization problems to generate scaffolds with optimal contiguity and correctness. Extensive experimental results demonstrate that our tool outperforms existing methods when multiple optical maps are available, and produces comparable scaffolds using a single optical map. OMGS can be obtained fromhttps://github.com/ucrbioinfo/OMGS


2017 ◽  
Author(s):  
Sebastien François ◽  
Rumen Andonov ◽  
Dominique Lavenier ◽  
Hristo Djidjev

AbstractWe describe a global optimization approach for genome assembly where the steps of scaffolding, gap-filling, and scaffold extension are simultaneously solved in the framework of a common objective function. The approach is based on integer programming model for solving genome scaffolding as a problem of finding a long simple path in a specific graph that satisfies additional constraints encoding the insert-size information. The optimal solution of this problem allows one to obtain new kind of contigs that we call distance-based contig. We test the algorithm on a benchmark of chloroplasts and compare the quality of the results with recent scaffolders.


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