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A Practical Comparison of De Novo Genome Assembly Software Tools for Next-Generation Sequencing Technologies

Overview of attention for article published in PLOS ONE, March 2011
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (94th percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

Mentioned by

blogs
2 blogs
twitter
4 X users
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16 patents
wikipedia
1 Wikipedia page
googleplus
1 Google+ user

Citations

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188 Dimensions

Readers on

mendeley
1134 Mendeley
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44 CiteULike
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Title
A Practical Comparison of De Novo Genome Assembly Software Tools for Next-Generation Sequencing Technologies
Published in
PLOS ONE, March 2011
DOI 10.1371/journal.pone.0017915
Pubmed ID
Authors

Wenyu Zhang, Jiajia Chen, Yang Yang, Yifei Tang, Jing Shang, Bairong Shen

Abstract

The advent of next-generation sequencing technologies is accompanied with the development of many whole-genome sequence assembly methods and software, especially for de novo fragment assembly. Due to the poor knowledge about the applicability and performance of these software tools, choosing a befitting assembler becomes a tough task. Here, we provide the information of adaptivity for each program, then above all, compare the performance of eight distinct tools against eight groups of simulated datasets from Solexa sequencing platform. Considering the computational time, maximum random access memory (RAM) occupancy, assembly accuracy and integrity, our study indicate that string-based assemblers, overlap-layout-consensus (OLC) assemblers are well-suited for very short reads and longer reads of small genomes respectively. For large datasets of more than hundred millions of short reads, De Bruijn graph-based assemblers would be more appropriate. In terms of software implementation, string-based assemblers are superior to graph-based ones, of which SOAPdenovo is complex for the creation of configuration file. Our comparison study will assist researchers in selecting a well-suited assembler and offer essential information for the improvement of existing assemblers or the developing of novel assemblers.

X Demographics

X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1,134 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 40 4%
United Kingdom 17 1%
Brazil 15 1%
France 14 1%
Germany 9 <1%
Spain 9 <1%
Netherlands 8 <1%
Canada 6 <1%
Sweden 6 <1%
Other 49 4%
Unknown 961 85%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 291 26%
Researcher 288 25%
Student > Master 174 15%
Student > Bachelor 77 7%
Other 60 5%
Other 173 15%
Unknown 71 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 709 63%
Biochemistry, Genetics and Molecular Biology 138 12%
Computer Science 97 9%
Engineering 17 1%
Medicine and Dentistry 14 1%
Other 72 6%
Unknown 87 8%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 23. 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 12 December 2023.
All research outputs
#1,454,855
of 23,577,654 outputs
Outputs from PLOS ONE
#18,720
of 202,026 outputs
Outputs of similar age
#5,826
of 109,931 outputs
Outputs of similar age from PLOS ONE
#148
of 1,398 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 202,026 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.3. This one has done particularly well, scoring higher than 90% 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 109,931 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 94% of its contemporaries.
We're also able to compare this research output to 1,398 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.