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An Integrated Tool to Study MHC Region: Accurate SNV Detection and HLA Genes Typing in Human MHC Region Using Targeted High-Throughput Sequencing

Overview of attention for article published in PLoS ONE, July 2013
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2 tweeters

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69 Mendeley
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Title
An Integrated Tool to Study MHC Region: Accurate SNV Detection and HLA Genes Typing in Human MHC Region Using Targeted High-Throughput Sequencing
Published in
PLoS ONE, July 2013
DOI 10.1371/journal.pone.0069388
Pubmed ID
Authors

Hongzhi Cao, Jinghua Wu, Yu Wang, Hui Jiang, Tao Zhang, Xiao Liu, Yinyin Xu, Dequan Liang, Peng Gao, Yepeng Sun, Benjamin Gifford, Mark D’Ascenzo, Xiaomin Liu, Laurent C. A. M. Tellier, Fang Yang, Xin Tong, Dan Chen, Jing Zheng, Weiyang Li, Todd Richmond, Xun Xu, Jun Wang, Yingrui Li

Abstract

The major histocompatibility complex (MHC) is one of the most variable and gene-dense regions of the human genome. Most studies of the MHC, and associated regions, focus on minor variants and HLA typing, many of which have been demonstrated to be associated with human disease susceptibility and metabolic pathways. However, the detection of variants in the MHC region, and diagnostic HLA typing, still lacks a coherent, standardized, cost effective and high coverage protocol of clinical quality and reliability. In this paper, we presented such a method for the accurate detection of minor variants and HLA types in the human MHC region, using high-throughput, high-coverage sequencing of target regions. A probe set was designed to template upon the 8 annotated human MHC haplotypes, and to encompass the 5 megabases (Mb) of the extended MHC region. We deployed our probes upon three, genetically diverse human samples for probe set evaluation, and sequencing data show that ∼97% of the MHC region, and over 99% of the genes in MHC region, are covered with sufficient depth and good evenness. 98% of genotypes called by this capture sequencing prove consistent with established HapMap genotypes. We have concurrently developed a one-step pipeline for calling any HLA type referenced in the IMGT/HLA database from this target capture sequencing data, which shows over 96% typing accuracy when deployed at 4 digital resolution. This cost-effective and highly accurate approach for variant detection and HLA typing in the MHC region may lend further insight into immune-mediated diseases studies, and may find clinical utility in transplantation medicine research. This one-step pipeline is released for general evaluation and use by the scientific community.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

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 %
United States 2 3%
Italy 1 1%
United Kingdom 1 1%
Brazil 1 1%
Spain 1 1%
Unknown 63 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 21 30%
Student > Ph. D. Student 11 16%
Student > Master 9 13%
Student > Bachelor 7 10%
Unspecified 6 9%
Other 15 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 31 45%
Biochemistry, Genetics and Molecular Biology 14 20%
Unspecified 8 12%
Engineering 4 6%
Immunology and Microbiology 4 6%
Other 8 12%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 01 August 2013.
All research outputs
#2,926,236
of 6,228,993 outputs
Outputs from PLoS ONE
#56,407
of 98,168 outputs
Outputs of similar age
#49,558
of 100,358 outputs
Outputs of similar age from PLoS ONE
#2,105
of 3,723 outputs
Altmetric has tracked 6,228,993 research outputs across all sources so far. This one is in the 29th percentile – i.e., 29% of other outputs scored the same or lower than it.
So far Altmetric has tracked 98,168 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.8. This one is in the 31st percentile – i.e., 31% 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 100,358 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 3,723 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.