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Scaffolding of long read assemblies using long range contact information

Overview of attention for article published in BMC Genomics, July 2017
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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 (83rd percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

Mentioned by

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20 tweeters
facebook
1 Facebook page

Citations

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134 Dimensions

Readers on

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204 Mendeley
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Title
Scaffolding of long read assemblies using long range contact information
Published in
BMC Genomics, July 2017
DOI 10.1186/s12864-017-3879-z
Pubmed ID
Authors

Jay Ghurye, Mihai Pop, Sergey Koren, Derek Bickhart, Chen-Shan Chin

Abstract

Long read technologies have revolutionized de novo genome assembly by generating contigs orders of magnitude longer than that of short read assemblies. Although assembly contiguity has increased, it usually does not reconstruct a full chromosome or an arm of the chromosome, resulting in an unfinished chromosome level assembly. To increase the contiguity of the assembly to the chromosome level, different strategies are used which exploit long range contact information between chromosomes in the genome. We develop a scalable and computationally efficient scaffolding method that can boost the assembly contiguity to a large extent using genome-wide chromatin interaction data such as Hi-C. we demonstrate an algorithm that uses Hi-C data for longer-range scaffolding of de novo long read genome assemblies. We tested our methods on the human and goat genome assemblies. We compare our scaffolds with the scaffolds generated by LACHESIS based on various metrics. Our new algorithm SALSA produces more accurate scaffolds compared to the existing state of the art method LACHESIS.

Twitter Demographics

The data shown below were collected from the profiles of 20 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 204 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 <1%
United States 1 <1%
Unknown 202 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 50 25%
Researcher 40 20%
Student > Master 27 13%
Student > Bachelor 17 8%
Student > Doctoral Student 9 4%
Other 21 10%
Unknown 40 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 81 40%
Biochemistry, Genetics and Molecular Biology 46 23%
Computer Science 14 7%
Chemistry 3 1%
Engineering 3 1%
Other 11 5%
Unknown 46 23%

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 07 March 2018.
All research outputs
#2,752,833
of 22,793,427 outputs
Outputs from BMC Genomics
#963
of 10,648 outputs
Outputs of similar age
#52,713
of 311,982 outputs
Outputs of similar age from BMC Genomics
#24
of 225 outputs
Altmetric has tracked 22,793,427 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,648 research outputs from this source. They receive a mean Attention Score of 4.7. 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 311,982 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 83% of its contemporaries.
We're also able to compare this research output to 225 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.