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Reference-guided de novo assembly approach improves genome reconstruction for related species

Overview of attention for article published in BMC Bioinformatics, November 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (80th percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

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Title
Reference-guided de novo assembly approach improves genome reconstruction for related species
Published in
BMC Bioinformatics, November 2017
DOI 10.1186/s12859-017-1911-6
Pubmed ID
Authors

Heidi E. L. Lischer, Kentaro K. Shimizu

Abstract

The development of next-generation sequencing has made it possible to sequence whole genomes at a relatively low cost. However, de novo genome assemblies remain challenging due to short read length, missing data, repetitive regions, polymorphisms and sequencing errors. As more and more genomes are sequenced, reference-guided assembly approaches can be used to assist the assembly process. However, previous methods mostly focused on the assembly of other genotypes within the same species. We adapted and extended a reference-guided de novo assembly approach, which enables the usage of a related reference sequence to guide the genome assembly. In order to compare and evaluate de novo and our reference-guided de novo assembly approaches, we used a simulated data set of a repetitive and heterozygotic plant genome. The extended reference-guided de novo assembly approach almost always outperforms the corresponding de novo assembly program even when a reference of a different species is used. Similar improvements can be observed in high and low coverage situations. In addition, we show that a single evaluation metric, like the widely used N50 length, is not enough to properly rate assemblies as it not always points to the best assembly evaluated with other criteria. Therefore, we used the summed z-scores of 36 different statistics to evaluate the assemblies. The combination of reference mapping and de novo assembly provides a powerful tool to improve genome reconstruction by integrating information of a related genome. Our extension of the reference-guided de novo assembly approach enables the application of this strategy not only within but also between related species. Finally, the evaluation of genome assemblies is often not straight forward, as the truth is not known. Thus one should always use a combination of evaluation metrics, which not only try to assess the continuity but also the accuracy of an assembly.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 507 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 507 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 100 20%
Researcher 79 16%
Student > Bachelor 72 14%
Student > Master 58 11%
Student > Doctoral Student 28 6%
Other 49 10%
Unknown 121 24%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 167 33%
Agricultural and Biological Sciences 142 28%
Immunology and Microbiology 16 3%
Computer Science 11 2%
Environmental Science 7 1%
Other 32 6%
Unknown 132 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 05 December 2023.
All research outputs
#3,628,243
of 25,002,811 outputs
Outputs from BMC Bioinformatics
#1,245
of 7,631 outputs
Outputs of similar age
#64,550
of 334,502 outputs
Outputs of similar age from BMC Bioinformatics
#17
of 137 outputs
Altmetric has tracked 25,002,811 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,631 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done well, scoring higher than 83% 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 334,502 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 80% of its contemporaries.
We're also able to compare this research output to 137 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.