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Evaluation of Different Reference Based Annotation Strategies Using RNA-Seq – A Case Study in Drososphila pseudoobscura

Overview of attention for article published in PLOS ONE, October 2012
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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)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

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Title
Evaluation of Different Reference Based Annotation Strategies Using RNA-Seq – A Case Study in Drososphila pseudoobscura
Published in
PLOS ONE, October 2012
DOI 10.1371/journal.pone.0046415
Pubmed ID
Authors

Nicola Palmieri, Viola Nolte, Anton Suvorov, Carolin Kosiol, Christian Schlötterer

Abstract

RNA-Seq is a powerful tool for the annotation of genomes, in particular for the identification of isoforms and UTRs. Nevertheless, several software tools exist and no standard strategy to obtain a reliable annotation is yet established. We tested different combinations of the most commonly used reference-based alignment tools (TopHat, GSNAP) in combination with two frequently used reference-based assemblers (Cufflinks, Scripture) and evaluated the potential of RNA-Seq to improve the annotation of Drosophila pseudoobscura. While GSNAP maps a higher proportion of reads, TopHat resulted in a more accurate annotation when used in combination with Cufflinks. Scripture had the lowest sensitivity. Interestingly, after subsampling to the same coverage for GSNAP and TopHat, we find that both mappers have similar performance, implying that the advantage of TopHat is mainly an artifact of the lower coverage. Overall, we observed a low concordance among the different approaches tested both at junction and isoform levels. Using data from both sexes of two adult strains of D. pseudoobscura we detected alternative splicing for about 30% of the FlyBase multiple-exon genes. Moreover, we extended the boundaries for 6523 genes (about 40%). We annotated 669 new genes, 45% of them with splicing evidence. Most of the new genes are located on unassembled contigs, reflecting their incomplete annotation. Finally, we identified 99 additional new genes that are not represented in the current genome contigs of D. pseudoobscura, probably due to location in genomic regions that are difficult to assemble (e.g. heterochromatic regions).

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 91 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 5%
United Kingdom 2 2%
Netherlands 1 1%
France 1 1%
Czechia 1 1%
Germany 1 1%
China 1 1%
Brazil 1 1%
Unknown 78 86%

Demographic breakdown

Readers by professional status Count As %
Researcher 33 36%
Student > Ph. D. Student 19 21%
Student > Master 8 9%
Student > Postgraduate 4 4%
Student > Bachelor 3 3%
Other 14 15%
Unknown 10 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 58 64%
Biochemistry, Genetics and Molecular Biology 18 20%
Computer Science 2 2%
Medicine and Dentistry 2 2%
Neuroscience 1 1%
Other 0 0%
Unknown 10 11%
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 21 December 2012.
All research outputs
#4,632,138
of 22,679,690 outputs
Outputs from PLOS ONE
#63,105
of 193,573 outputs
Outputs of similar age
#34,114
of 172,465 outputs
Outputs of similar age from PLOS ONE
#1,019
of 4,541 outputs
Altmetric has tracked 22,679,690 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 193,573 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.0. This one has gotten more attention than average, scoring higher than 67% 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 172,465 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 4,541 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.