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Improving alignment accuracy on homopolymer regions for semiconductor-based sequencing technologies

Overview of attention for article published in BMC Genomics, August 2016
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3 X users

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25 Dimensions

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33 Mendeley
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Title
Improving alignment accuracy on homopolymer regions for semiconductor-based sequencing technologies
Published in
BMC Genomics, August 2016
DOI 10.1186/s12864-016-2894-9
Pubmed ID
Authors

Weixing Feng, Sen Zhao, Dingkai Xue, Fengfei Song, Ziwei Li, Duojiao Chen, Bo He, Yangyang Hao, Yadong Wang, Yunlong Liu

Abstract

Ion Torrent and Ion Proton are semiconductor-based sequencing technologies that feature rapid sequencing speed and low upfront and operating costs, thanks to the avoidance of modified nucleotides and optical measurements. Despite of these advantages, however, Ion semiconductor sequencing technologies suffer much reduced sequencing accuracy at the genomic loci with homopolymer repeats of the same nucleotide. Such limitation significantly reduces its efficiency for the biological applications aiming at accurately identifying various genetic variants. In this study, we propose a Bayesian inference-based method that takes the advantage of the signal distributions of the electrical voltages that are measured for all the homopolymers of a fixed length. By cross-referencing the length of homopolymers in the reference genome and the voltage signal distribution derived from the experiment, the proposed integrated model significantly improves the alignment accuracy around the homopolymer regions. Besides improving alignment accuracy on homopolymer regions for semiconductor-based sequencing technologies with the proposed model, similar strategies can also be used on other high-throughput sequencing technologies that share similar limitations.

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The data shown below were collected from the profiles of 3 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 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 33 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 10 30%
Student > Ph. D. Student 4 12%
Researcher 3 9%
Student > Bachelor 3 9%
Other 2 6%
Other 2 6%
Unknown 9 27%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 15 45%
Agricultural and Biological Sciences 6 18%
Medicine and Dentistry 3 9%
Neuroscience 1 3%
Unknown 8 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 25 August 2016.
All research outputs
#13,986,767
of 22,883,326 outputs
Outputs from BMC Genomics
#5,356
of 10,668 outputs
Outputs of similar age
#192,432
of 343,744 outputs
Outputs of similar age from BMC Genomics
#126
of 273 outputs
Altmetric has tracked 22,883,326 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,668 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 46th percentile – i.e., 46% of its peers scored the same or lower than it.
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 343,744 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 273 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.