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SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler

Overview of attention for article published in Giga Science, December 2012
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#49 of 746)
  • High Attention Score compared to outputs of the same age (98th percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

Mentioned by

blogs
3 blogs
twitter
60 tweeters
patent
1 patent
peer_reviews
2 peer review sites
facebook
1 Facebook page
wikipedia
1 Wikipedia page
googleplus
2 Google+ users
f1000
1 research highlight platform

Readers on

mendeley
1561 Mendeley
citeulike
9 CiteULike
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Title
SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler
Published in
Giga Science, December 2012
DOI 10.1186/2047-217x-1-18
Pubmed ID
Authors

Ruibang Luo, Binghang Liu, Yinlong Xie, Zhenyu Li, Weihua Huang, Jianying Yuan, Guangzhu He, Yanxiang Chen, Qi Pan, Yunjie Liu, Jingbo Tang, Gengxiong Wu, Hao Zhang, Yujian Shi, Yong Liu, Chang Yu, Bo Wang, Yao Lu, Changlei Han, David W Cheung, Siu-Ming Yiu, Shaoliang Peng, Zhu Xiaoqian, Guangming Liu, Xiangke Liao, Yingrui Li, Huanming Yang, Jian Wang, Tak-Wah Lam, Jun Wang

Abstract

There 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. To 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. Benchmark 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.

Twitter Demographics

The data shown below were collected from the profiles of 60 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 1,561 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 19 1%
Germany 15 <1%
Brazil 13 <1%
France 9 <1%
United Kingdom 8 <1%
Spain 6 <1%
Netherlands 6 <1%
Italy 6 <1%
Japan 5 <1%
Other 52 3%
Unknown 1422 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 424 27%
Researcher 320 20%
Student > Master 235 15%
Student > Bachelor 144 9%
Student > Doctoral Student 83 5%
Other 245 16%
Unknown 110 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 895 57%
Biochemistry, Genetics and Molecular Biology 263 17%
Computer Science 102 7%
Environmental Science 32 2%
Engineering 23 1%
Other 96 6%
Unknown 150 10%

Attention Score in Context

This research output has an Altmetric Attention Score of 62. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 July 2020.
All research outputs
#349,967
of 15,488,552 outputs
Outputs from Giga Science
#49
of 746 outputs
Outputs of similar age
#4,193
of 261,102 outputs
Outputs of similar age from Giga Science
#4
of 17 outputs
Altmetric has tracked 15,488,552 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 746 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 23.2. This one has done particularly well, scoring higher than 93% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 261,102 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 98% of its contemporaries.
We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.