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Challenges imposed by minor reference alleles on the identification and reporting of clinical variants from exome data

Overview of attention for article published in BMC Genomics, January 2018
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Title
Challenges imposed by minor reference alleles on the identification and reporting of clinical variants from exome data
Published in
BMC Genomics, January 2018
DOI 10.1186/s12864-018-4433-3
Pubmed ID
Authors

Mahmoud Koko, Mohammed O. E. Abdallah, Mutaz Amin, Muntaser Ibrahim

Abstract

The conventional variant calling of pathogenic alleles in exome and genome sequencing requires the presence of the non-pathogenic alleles as genome references. This hinders the correct identification of variants with minor and/or pathogenic reference alleles warranting additional approaches for variant calling. More than 26,000 Exome Aggregation Consortium (ExAC) variants have a minor reference allele including variants with known ClinVar disease alleles. For instance, in a number of variants related to clotting disorders, the phenotype-associated allele is a human genome reference allele (rs6025, rs6003, rs1799983, and rs2227564 using the assembly hg19). We highlighted how the current variant calling standards miss homozygous reference disease variants in these sites and provided a bioinformatic panel that can be used to screen these variants using commonly available variant callers. We present exome sequencing results from an individual with venous thrombosis to emphasize how pathogenic alleles in clinically relevant variants escape variant calling while non-pathogenic alleles are detected. This article highlights the importance of specialized variant calling strategies in clinical variants with minor reference alleles especially in the context of personal genomes and exomes. We provide here a simple strategy to screen potential disease-causing variants when present in homozygous reference state.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 53 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 21%
Student > Master 11 21%
Researcher 7 13%
Student > Doctoral Student 6 11%
Unspecified 2 4%
Other 8 15%
Unknown 8 15%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 19 36%
Agricultural and Biological Sciences 11 21%
Medicine and Dentistry 7 13%
Unspecified 2 4%
Business, Management and Accounting 1 2%
Other 4 8%
Unknown 9 17%
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 14 November 2019.
All research outputs
#14,708,000
of 24,666,614 outputs
Outputs from BMC Genomics
#5,289
of 11,035 outputs
Outputs of similar age
#248,304
of 484,467 outputs
Outputs of similar age from BMC Genomics
#110
of 217 outputs
Altmetric has tracked 24,666,614 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,035 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 49th percentile – i.e., 49% of its peers scored the same or lower than it.
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We're also able to compare this research output to 217 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.