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Analytical parameters and validation of homopolymer detection in a pyrosequencing-based next generation sequencing system

Overview of attention for article published in BMC Genomics, February 2018
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Title
Analytical parameters and validation of homopolymer detection in a pyrosequencing-based next generation sequencing system
Published in
BMC Genomics, February 2018
DOI 10.1186/s12864-018-4544-x
Pubmed ID
Authors

Gergely Ivády, László Madar, Erika Dzsudzsák, Katalin Koczok, János Kappelmayer, Veronika Krulisova, Milan Macek, Attila Horváth, István Balogh

Abstract

Current technologies in next-generation sequencing are offering high throughput reads at low costs, but still suffer from various sequencing errors. Although pyro- and ion semiconductor sequencing both have the advantage of delivering long and high quality reads, problems might occur when sequencing homopolymer-containing regions, since the repeating identical bases are going to incorporate during the same synthesis cycle, which leads to uncertainty in base calling. The aim of this study was to evaluate the analytical performance of a pyrosequencing-based next-generation sequencing system in detecting homopolymer sequences using homopolymer-preintegrated plasmid constructs and human DNA samples originating from patients with cystic fibrosis. In the plasmid system average correct genotyping was 95.8% in 4-mers, 87.4% in 5-mers and 72.1% in 6-mers. Despite the experienced low genotyping accuracy in 5- and 6-mers, it was possible to generate amplicons with more than a 90% adequate detection rate in every homopolymer tract. When homopolymers in the CFTR gene were sequenced average accuracy was 89.3%, but varied in a wide range (52.2 - 99.1%). In all but one case, an optimal amplicon-sequencing primer combination could be identified. In that single case (7A tract in exon 14 (c.2046_2052)), none of the tested primer sets produced the required analytical performance. Our results show that pyrosequencing is the most reliable in case of 4-mers and as homopolymer length gradually increases, accuracy deteriorates. With careful primer selection, the NGS system was able to correctly genotype all but one of the homopolymers in the CFTR gene. In conclusion, we configured a plasmid test system that can be used to assess genotyping accuracy of NGS devices and developed an accurate NGS assay for the molecular diagnosis of CF using self-designed primers for amplification and sequencing.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 59 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 15%
Student > Ph. D. Student 8 14%
Student > Bachelor 8 14%
Student > Master 8 14%
Other 3 5%
Other 9 15%
Unknown 14 24%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 10 17%
Agricultural and Biological Sciences 8 14%
Immunology and Microbiology 4 7%
Computer Science 3 5%
Unspecified 3 5%
Other 14 24%
Unknown 17 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 11 June 2022.
All research outputs
#13,920,963
of 23,848,132 outputs
Outputs from BMC Genomics
#4,956
of 10,839 outputs
Outputs of similar age
#170,103
of 334,230 outputs
Outputs of similar age from BMC Genomics
#92
of 187 outputs
Altmetric has tracked 23,848,132 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,839 research outputs from this source. They receive a mean Attention Score of 4.8. This one has gotten more attention than average, scoring higher than 52% 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 334,230 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 187 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.