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Benchmarking the HLA typing performance of Polysolver and Optitype in 50 Danish parental trios

Overview of attention for article published in BMC Bioinformatics, June 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 (80th percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

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Title
Benchmarking the HLA typing performance of Polysolver and Optitype in 50 Danish parental trios
Published in
BMC Bioinformatics, June 2018
DOI 10.1186/s12859-018-2239-6
Pubmed ID
Authors

Maria Luisa Matey-Hernandez, Danish Pan Genome Consortium, Søren Brunak, Jose M. G. Izarzugaza

Abstract

The adaptive immune response intrinsically depends on hypervariable human leukocyte antigen (HLA) genes. Concomitantly, correct HLA phenotyping is crucial for successful donor-patient matching in organ transplantation. The cost and technical limitations of current laboratory techniques, together with advances in next-generation sequencing (NGS) methodologies, have increased the need for precise computational typing methods. We tested two widespread HLA typing methods using high quality full genome sequencing data from 150 individuals in 50 family trios from the Genome Denmark project. First, we computed descendant accuracies assessing the agreement in the inheritance of alleles from parents to offspring. Second, we compared the locus-specific homozygosity rates as well as the allele frequencies; and we compared those to the observed values in related populations. We provide guidelines for testing the accuracy of HLA typing methods by comparing family information, which is independent of the availability of curated alleles. Although current computational methods for HLA typing generally provide satisfactory results, our benchmark - using data with ultra-high sequencing depth - demonstrates the incompleteness of current reference databases, and highlights the importance of providing genomic databases addressing current sequencing standards, a problem yet to be resolved before benefiting fully from personalised medicine approaches HLA phenotyping is essential.

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X Demographics

The data shown below were collected from the profiles of 16 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 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 69 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 22%
Student > Ph. D. Student 13 19%
Student > Master 9 13%
Student > Bachelor 5 7%
Other 4 6%
Other 7 10%
Unknown 16 23%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 16 23%
Computer Science 11 16%
Agricultural and Biological Sciences 9 13%
Medicine and Dentistry 8 12%
Immunology and Microbiology 2 3%
Other 6 9%
Unknown 17 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 14 February 2019.
All research outputs
#2,987,526
of 23,092,602 outputs
Outputs from BMC Bioinformatics
#1,059
of 7,328 outputs
Outputs of similar age
#63,582
of 328,981 outputs
Outputs of similar age from BMC Bioinformatics
#18
of 97 outputs
Altmetric has tracked 23,092,602 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,328 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 well, scoring higher than 85% 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 328,981 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 97 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.