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ITIS, a bioinformatics tool for accurate identification of transposon insertion sites using next-generation sequencing data

Overview of attention for article published in BMC Bioinformatics, March 2015
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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 (89th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

blogs
1 blog
twitter
13 X users
weibo
1 weibo user
facebook
1 Facebook page

Citations

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55 Dimensions

Readers on

mendeley
140 Mendeley
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1 CiteULike
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Title
ITIS, a bioinformatics tool for accurate identification of transposon insertion sites using next-generation sequencing data
Published in
BMC Bioinformatics, March 2015
DOI 10.1186/s12859-015-0507-2
Pubmed ID
Authors

Chuan Jiang, Chao Chen, Ziyue Huang, Renyi Liu, Jerome Verdier

Abstract

Transposable elements constitute an important part of the genome and are essential in adaptive mechanisms. Transposition events associated with phenotypic changes occur naturally or are induced in insertional mutant populations. Transposon mutagenesis results in multiple random insertions and recovery of most/all the insertions is critical for forward genetics study. Using genome next-generation sequencing data and appropriate bioinformatics tool, it is plausible to accurately identify transposon insertion sites, which could provide candidate causal mutations for desired phenotypes for further functional validation. We developed a novel bioinformatics tool, ITIS (Identification of Transposon Insertion Sites), for localizing transposon insertion sites within a genome. It takes next-generation genome re-sequencing data (NGS data), transposon sequence, and reference genome sequence as input, and generates a list of highly reliable candidate insertion sites as well as zygosity information of each insertion. Using a simulated dataset and a case study based on an insertional mutant line from Medicago truncatula, we showed that ITIS performed better in terms of sensitivity and specificity than other similar algorithms such as RelocaTE, RetroSeq, TEMP and TIF. With the case study data, we demonstrated the efficiency of ITIS by validating the presence and zygosity of predicted insertion sites of the Tnt1 transposon within a complex plant system, M. truncatula. This study showed that ITIS is a robust and powerful tool for forward genetic studies in identifying transposable element insertions causing phenotypes. ITIS is suitable in various systems such as cell culture, bacteria, yeast, insect, mammal and plant.

X Demographics

X Demographics

The data shown below were collected from the profiles of 13 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 140 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 2 1%
Netherlands 2 1%
France 2 1%
Chile 1 <1%
Germany 1 <1%
Norway 1 <1%
Israel 1 <1%
United Kingdom 1 <1%
Canada 1 <1%
Other 0 0%
Unknown 128 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 33 24%
Student > Ph. D. Student 31 22%
Student > Master 24 17%
Student > Bachelor 11 8%
Student > Postgraduate 8 6%
Other 17 12%
Unknown 16 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 69 49%
Biochemistry, Genetics and Molecular Biology 20 14%
Computer Science 11 8%
Medicine and Dentistry 5 4%
Immunology and Microbiology 3 2%
Other 11 8%
Unknown 21 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 17. 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 03 September 2015.
All research outputs
#2,022,602
of 23,577,761 outputs
Outputs from BMC Bioinformatics
#496
of 7,400 outputs
Outputs of similar age
#26,498
of 259,209 outputs
Outputs of similar age from BMC Bioinformatics
#5
of 137 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,400 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done particularly well, scoring higher than 93% 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 259,209 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 89% 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 particularly well, scoring higher than 96% of its contemporaries.