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SoftSearch: Integration of Multiple Sequence Features to Identify Breakpoints of Structural Variations

Overview of attention for article published in PLOS ONE, December 2013
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Title
SoftSearch: Integration of Multiple Sequence Features to Identify Breakpoints of Structural Variations
Published in
PLOS ONE, December 2013
DOI 10.1371/journal.pone.0083356
Pubmed ID
Authors

Steven N. Hart, Vivekananda Sarangi, Raymond Moore, Saurabh Baheti, Jaysheel D. Bhavsar, Fergus J. Couch, Jean-Pierre A. Kocher

Abstract

Structural variation (SV) represents a significant, yet poorly understood contribution to an individual's genetic makeup. Advanced next-generation sequencing technologies are widely used to discover such variations, but there is no single detection tool that is considered a community standard. In an attempt to fulfil this need, we developed an algorithm, SoftSearch, for discovering structural variant breakpoints in Illumina paired-end next-generation sequencing data. SoftSearch combines multiple strategies for detecting SV including split-read, discordant read-pair, and unmated pairs. Co-localized split-reads and discordant read pairs are used to refine the breakpoints.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 3 4%
United States 3 4%
Italy 2 3%
Sweden 1 1%
Germany 1 1%
Ukraine 1 1%
South Africa 1 1%
Unknown 58 83%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 22 31%
Researcher 17 24%
Student > Master 8 11%
Other 4 6%
Student > Bachelor 4 6%
Other 8 11%
Unknown 7 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 28 40%
Biochemistry, Genetics and Molecular Biology 15 21%
Computer Science 8 11%
Medicine and Dentistry 3 4%
Mathematics 1 1%
Other 5 7%
Unknown 10 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 22 October 2014.
All research outputs
#17,708,224
of 22,738,543 outputs
Outputs from PLOS ONE
#146,721
of 194,081 outputs
Outputs of similar age
#223,351
of 307,527 outputs
Outputs of similar age from PLOS ONE
#3,870
of 5,492 outputs
Altmetric has tracked 22,738,543 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 194,081 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.1. This one is in the 20th percentile – i.e., 20% of its peers scored the same or lower than it.
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We're also able to compare this research output to 5,492 others from the same source and published within six weeks on either side of this one. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.