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Combining de novo and reference-guided assembly with scaffold_builder

Overview of attention for article published in Source Code for Biology and Medicine, November 2013
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#27 of 127)
  • High Attention Score compared to outputs of the same age (81st percentile)

Mentioned by

twitter
7 X users
wikipedia
1 Wikipedia page

Citations

dimensions_citation
59 Dimensions

Readers on

mendeley
199 Mendeley
citeulike
3 CiteULike
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Title
Combining de novo and reference-guided assembly with scaffold_builder
Published in
Source Code for Biology and Medicine, November 2013
DOI 10.1186/1751-0473-8-23
Pubmed ID
Authors

Genivaldo GZ Silva, Bas E Dutilh, T David Matthews, Keri Elkins, Robert Schmieder, Elizabeth A Dinsdale, Robert A Edwards

Abstract

Genome sequencing has become routine, however genome assembly still remains a challenge despite the computational advances in the last decade. In particular, the abundance of repeat elements in genomes makes it difficult to assemble them into a single complete sequence. Identical repeats shorter than the average read length can generally be assembled without issue. However, longer repeats such as ribosomal RNA operons cannot be accurately assembled using existing tools. The application Scaffold_builder was designed to generate scaffolds - super contigs of sequences joined by N-bases - based on the similarity to a closely related reference sequence. This is independent of mate-pair information and can be used complementarily for genome assembly, e.g. when mate-pairs are not available or have already been exploited. Scaffold_builder was evaluated using simulated pyrosequencing reads of the bacterial genomes Escherichia coli 042, Lactobacillus salivarius UCC118 and Salmonella enterica subsp. enterica serovar Typhi str. P-stx-12. Moreover, we sequenced two genomes from Salmonella enterica serovar Typhimurium LT2 G455 and Salmonella enterica serovar Typhimurium SDT1291 and show that Scaffold_builder decreases the number of contig sequences by 53% while more than doubling their average length. Scaffold_builder is written in Python and is available at http://edwards.sdsu.edu/scaffold_builder. A web-based implementation is additionally provided to allow users to submit a reference genome and a set of contigs to be scaffolded.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 199 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 3%
Germany 3 2%
Netherlands 2 1%
France 2 1%
Sweden 2 1%
Portugal 1 <1%
Vietnam 1 <1%
Italy 1 <1%
Norway 1 <1%
Other 4 2%
Unknown 177 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 52 26%
Researcher 47 24%
Student > Master 32 16%
Student > Bachelor 14 7%
Student > Postgraduate 7 4%
Other 29 15%
Unknown 18 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 104 52%
Biochemistry, Genetics and Molecular Biology 42 21%
Computer Science 13 7%
Immunology and Microbiology 4 2%
Medicine and Dentistry 2 1%
Other 9 5%
Unknown 25 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 November 2018.
All research outputs
#4,715,116
of 23,577,654 outputs
Outputs from Source Code for Biology and Medicine
#27
of 127 outputs
Outputs of similar age
#54,395
of 305,983 outputs
Outputs of similar age from Source Code for Biology and Medicine
#1
of 3 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 127 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one has done well, scoring higher than 78% 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 305,983 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 81% of its contemporaries.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them