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Determining multiallelic complex copy number and sequence variation from high coverage exome sequencing data

Overview of attention for article published in BMC Genomics, November 2015
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (54th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (57th percentile)

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6 X users

Citations

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3 Dimensions

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30 Mendeley
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Title
Determining multiallelic complex copy number and sequence variation from high coverage exome sequencing data
Published in
BMC Genomics, November 2015
DOI 10.1186/s12864-015-2123-y
Pubmed ID
Authors

Diego Forni, Diana Martin, Razan Abujaber, Andrew J. Sharp, Manuela Sironi, Edward J. Hollox

Abstract

Copy number variation (CNV) is a major component of genomic variation, yet methods to accurately type genomic CNV lag behind methods that type single nucleotide variation. High-throughput sequencing can contribute to these methods by using sequence read depth, which takes the number of reads that map to a given part of the reference genome as a proxy for copy number of that region, and compares across samples. Furthermore, high-throughput sequencing also provides information on the sequence differences between copies within and between individuals. In this study we use high-coverage phase 3 exome sequences of the 1000 Genomes project to infer diploid copy number of the beta-defensin genomic region, a well-studied CNV that carries several beta-defensin genes involved in the antimicrobial response, signalling, and fertility. We also use these data to call sequence variants, a particular challenge given the multicopy nature of the region. We confidently call copy number and sequence variation of the beta-defensin genes on 1285 samples from 26 global populations, validate copy number using Nanostring nCounter and triplex paralogue ratio test data. We use the copy number calls to verify the genomic extent of the CNV and validate sequence calls using analysis of cloned PCR products. We identify novel variation, mostly individually rare, predicted to alter amino-acid sequence in the beta-defensin genes. Such novel variants may alter antimicrobial properties or have off-target receptor interactions, and may contribute to individuality in immunological response and fertility. Given that 81 % of identified sequence variants were not previously in dbSNP, we show that sequence variation in multiallelic CNVs represent an unappreciated source of genomic diversity.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 3%
Unknown 29 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 37%
Researcher 4 13%
Student > Bachelor 3 10%
Student > Master 3 10%
Student > Postgraduate 2 7%
Other 6 20%
Unknown 1 3%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 43%
Biochemistry, Genetics and Molecular Biology 10 33%
Computer Science 1 3%
Immunology and Microbiology 1 3%
Medicine and Dentistry 1 3%
Other 2 7%
Unknown 2 7%
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 12 November 2015.
All research outputs
#13,944,366
of 24,666,614 outputs
Outputs from BMC Genomics
#4,657
of 11,035 outputs
Outputs of similar age
#130,290
of 290,843 outputs
Outputs of similar age from BMC Genomics
#154
of 385 outputs
Altmetric has tracked 24,666,614 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% 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 has gotten more attention than average, scoring higher than 56% 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 290,843 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 54% of its contemporaries.
We're also able to compare this research output to 385 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 57% of its contemporaries.