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Inferring synteny between genome assemblies: a systematic evaluation

Overview of attention for article published in BMC Bioinformatics, January 2018
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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 (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

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49 X users
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2 Wikipedia pages

Citations

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94 Dimensions

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346 Mendeley
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Title
Inferring synteny between genome assemblies: a systematic evaluation
Published in
BMC Bioinformatics, January 2018
DOI 10.1186/s12859-018-2026-4
Pubmed ID
Authors

Dang Liu, Martin Hunt, Isheng J Tsai

Abstract

Genome assemblies across all domains of life are being produced routinely. Initial analysis of a new genome usually includes annotation and comparative genomics. Synteny provides a framework in which conservation of homologous genes and gene order is identified between genomes of different species. The availability of human and mouse genomes paved the way for algorithm development in large-scale synteny mapping, which eventually became an integral part of comparative genomics. Synteny analysis is regularly performed on assembled sequences that are fragmented, neglecting the fact that most methods were developed using complete genomes. It is unknown to what extent draft assemblies lead to errors in such analysis. We fragmented genome assemblies of model nematodes to various extents and conducted synteny identification and downstream analysis. We first show that synteny between species can be underestimated up to 40% and find disagreements between popular tools that infer synteny blocks. This inconsistency and further demonstration of erroneous gene ontology enrichment tests raise questions about the robustness of previous synteny analysis when gold standard genome sequences remain limited. In addition, assembly scaffolding using a reference guided approach with a closely related species may result in chimeric scaffolds with inflated assembly metrics if a true evolutionary relationship was overlooked. Annotation quality, however, has minimal effect on synteny if the assembled genome is highly contiguous. Our results show that a minimum N50 of 1 Mb is required for robust downstream synteny analysis, which emphasizes the importance of gold standard genomes to the science community, and should be achieved given the current progress in sequencing technology.

X Demographics

X Demographics

The data shown below were collected from the profiles of 49 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 346 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 346 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 68 20%
Researcher 63 18%
Student > Bachelor 53 15%
Student > Master 39 11%
Student > Doctoral Student 21 6%
Other 35 10%
Unknown 67 19%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 112 32%
Agricultural and Biological Sciences 112 32%
Computer Science 12 3%
Environmental Science 7 2%
Business, Management and Accounting 4 1%
Other 18 5%
Unknown 81 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 29. 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 19 December 2022.
All research outputs
#1,365,777
of 25,728,855 outputs
Outputs from BMC Bioinformatics
#153
of 7,738 outputs
Outputs of similar age
#31,509
of 451,544 outputs
Outputs of similar age from BMC Bioinformatics
#4
of 123 outputs
Altmetric has tracked 25,728,855 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,738 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. This one has done particularly well, scoring higher than 98% 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 451,544 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 93% of its contemporaries.
We're also able to compare this research output to 123 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.