ArticleGigaScience2012
SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler.
Article in GigaScience, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2,802 papers.
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Who cites it
2,802 citing papers in PubMed.
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2,742 more citing papers are in PubMed but not listed here.
Corrections and comments
- Erratum issued
Authors and funding
30 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThere is a rapidly increasing amount of de novo genome assembly using next-generation sequencing (NGS) short reads; however, several big challenges remain to be overcome in order for this to be efficient and accurate. SOAPdenovo has been successfully applied to assemble many published genomes, but it still needs improvement in continuity, accuracy and coverage, especially in repeat regions.
findingsTo overcome these challenges, we have developed its successor, SOAPdenovo2, which has the advantage of a new algorithm design that reduces memory consumption in graph construction, resolves more repeat regions in contig assembly, increases coverage and length in scaffold construction, improves gap closing, and optimizes for large genome.
conclusionsBenchmark using the Assemblathon1 and GAGE datasets showed that SOAPdenovo2 greatly surpasses its predecessor SOAPdenovo and is competitive to other assemblers on both assembly length and accuracy. We also provide an updated assembly version of the 2008 Asian (YH) genome using SOAPdenovo2. Here, the contig and scaffold N50 of the YH genome were ~20.9 kbp and ~22 Mbp, respectively, which is 3-fold and 50-fold longer than the first published version. The genome coverage increased from 81.16% to 93.91%, and memory consumption was ~2/3 lower during the point of largest memory consumption.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.