scholarly journals SWAP-Assembler 2: Optimization of De Novo Genome Assembler at Extreme Scale

2016 ◽  
Author(s):  
Jintao Meng ◽  
Sangmin Seo ◽  
Pavan Balaji ◽  
Yanjie Wei ◽  
Bingqiang Wang ◽  
...  
Keyword(s):  
De Novo ◽  
Extreme Scale ◽  
Genome Assembler

scholarly journals rnaSPAdes: a de novo transcriptome assembler and its application to RNA-Seq data

2018 ◽  
Author(s):  
Elena Bushmanova ◽  
Dmitry Antipov ◽  
Alla Lapidus ◽  
Andrey D. Prjibelski
Keyword(s):  
De Novo ◽  
Transcriptome Assembly ◽  
Model Organisms ◽  
Challenging Problem ◽  
Rna Seq ◽  
De Novo Transcriptome ◽  
Weak Points ◽  
Transcriptome Reconstruction ◽  
Evaluation Approaches ◽  
Genome Assembler

AbstractSummaryPossibility to generate large RNA-seq datasets has led to development of various reference-based and de novo transcriptome assemblers with their own strengths and limitations. While reference-based tools are widely used in various transcriptomic studies, their application is limited to the model organisms with finished and annotated genomes. De novo transcriptome reconstruction from short reads remains an open challenging problem, which is complicated by the varying expression levels across different genes, alternative splicing and paralogous genes. In this paper we describe a novel transcriptome assembler called rnaSPAdes, which is developed on top of SPAdes genome assembler and explores surprising computational parallels between assembly of transcriptomes and single-cell genomes. We also present quality assessment reports for rnaSPAdes assemblies, compare it with modern transcriptome assembly tools using several evaluation approaches on various RNA-Seq datasets, and briefly highlight strong and weak points of different assemblers.Availability and implementationrnaSPAdes is implemented in C++ and Python and is freely available at cab.spbu.ru/software/rnaspades/.

scholarly journals Raven: a de novo genome assembler for long reads

2020 ◽  
Author(s):  
Robert Vaser ◽  
Mile Šikić
Keyword(s):  
Human Genome ◽  
Genome Assembly ◽  
De Novo ◽  
De Novo Genome Assembly ◽  
New Methods ◽  
Long Reads ◽  
Long Read ◽  
Comparable Accuracy ◽  
Genome Assembler ◽  
Genome Dataset

We present new methods for the improvement of long-read de novo genome assembly incorporated into a straightforward tool called Raven (https://github.com/lbcb-sci/raven). Compared with other assemblers, Raven is one of two fastest, it reconstructs the sequenced genome in the least amount of fragments, has better or comparable accuracy, and maintains similar performance for various genomes. Raven takes 500 CPU hours to assemble a 44x human genome dataset in only 259 fragments.

scholarly journals Extreme-Scale De Novo Genome Assembly

2017 ◽  
pp. 409-430 ◽  
Author(s):  
Evangelos Georganas ◽  
Steven Hofmeyr ◽  
Leonid Oliker ◽  
Rob Egan ◽  
Daniel Rokhsar ◽  
...  
Keyword(s):  
Genome Assembly ◽  
De Novo ◽  
De Novo Genome Assembly ◽  
Extreme Scale

scholarly journals Extreme Scale De Novo Metagenome Assembly

2018 ◽  
Author(s):  
Evangelos Georganas ◽  
Rob Egan ◽  
Steven Hofmeyr ◽  
Eugene Goltsman ◽  
Bill Arndt ◽  
...  
Keyword(s):  
De Novo ◽  
Metagenome Assembly ◽  
Extreme Scale

scholarly journals RepAHR: an improved approach for de novo repeat identification by assembly of the high-frequency reads

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Xingyu Liao ◽  
Xin Gao ◽  
Xiankai Zhang ◽  
Fang-Xiang Wu ◽  
Jianxin Wang
Keyword(s):  
High Frequency ◽  
Structural Variation ◽  
De Novo ◽  
Repetitive Sequences ◽  
Data Sets ◽  
Sequence Coverage ◽  
Coverage Ratio ◽  
Next Generation Sequencing Ngs ◽  
Genome Assembler ◽  
Generation Sequencing

Abstract Background Repetitive sequences account for a large proportion of eukaryotes genomes. Identification of repetitive sequences plays a significant role in many applications, such as structural variation detection and genome assembly. Many existing de novo repeat identification pipelines or tools make use of assembly of the high-frequency k-mers to obtain repeats. However, a certain degree of sequence coverage is required for assemblers to get the desired assemblies. On the other hand, assemblers cut the reads into shorter k-mers for assembly, which may destroy the structure of the repetitive regions. For the above reasons, it is difficult to obtain complete and accurate repetitive regions in the genome by using existing tools. Results In this study, we present a new method called RepAHR for de novo repeat identification by assembly of the high-frequency reads. Firstly, RepAHR scans next-generation sequencing (NGS) reads to find the high-frequency k-mers. Secondly, RepAHR filters the high-frequency reads from whole NGS reads according to certain rules based on the high-frequency k-mer. Finally, the high-frequency reads are assembled to generate repeats by using SPAdes, which is considered as an outstanding genome assembler with NGS sequences. Conlusions We test RepAHR on five data sets, and the experimental results show that RepAHR outperforms RepARK and REPdenovo for detecting repeats in terms of N50, reference alignment ratio, coverage ratio of reference, mask ratio of Repbase and some other metrics.

scholarly journals Integrative Meta-Assembly Pipeline (IMAP): Chromosome-level genome assembler combining multiple de novo assemblies

PLoS ONE ◽  
2019 ◽  
Vol 14 (8) ◽  
pp. e0221858 ◽  
Author(s):  
Giltae Song ◽  
Jongin Lee ◽  
Juyeon Kim ◽  
Seokwoo Kang ◽  
Hoyong Lee ◽  
...  
Keyword(s):  
De Novo ◽  
Assembly Pipeline ◽  
Genome Assembler ◽  
Chromosome Level

scholarly journals rnaSPAdes: a de novo transcriptome assembler and its application to RNA-Seq data

GigaScience ◽  
2019 ◽  
Vol 8 (9) ◽  
Author(s):  
Elena Bushmanova ◽  
Dmitry Antipov ◽  
Alla Lapidus ◽  
Andrey D Prjibelski
Keyword(s):  
Rna Sequencing ◽  
De Novo ◽  
Transcriptome Assembly ◽  
The Novel ◽  
Rna Seq ◽  
De Novo Transcriptome ◽  
Weak Points ◽  
Transcriptome Reconstruction ◽  
Evaluation Approaches ◽  
Genome Assembler

Abstract Background The possibility of generating large RNA-sequencing datasets has led to development of various reference-based and de novo transcriptome assemblers with their own strengths and limitations. While reference-based tools are widely used in various transcriptomic studies, their application is limited to the organisms with finished and well-annotated genomes. De novo transcriptome reconstruction from short reads remains an open challenging problem, which is complicated by the varying expression levels across different genes, alternative splicing, and paralogous genes. Results Herein we describe the novel transcriptome assembler rnaSPAdes, which has been developed on top of the SPAdes genome assembler and explores computational parallels between assembly of transcriptomes and single-cell genomes. We also present quality assessment reports for rnaSPAdes assemblies, compare it with modern transcriptome assembly tools using several evaluation approaches on various RNA-sequencing datasets, and briefly highlight strong and weak points of different assemblers. Conclusions Based on the performed comparison between different assembly methods, we infer that it is not possible to detect the absolute leader according to all quality metrics and all used datasets. However, rnaSPAdes typically outperforms other assemblers by such important property as the number of assembled genes and isoforms, and at the same time has higher accuracy statistics on average comparing to the closest competitors.

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