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Technical considerations for genotyping multi-allelic copy number variation (CNV), in regions of segmental duplication

Overview of attention for article published in BMC Genomics, May 2014
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2 X users

Citations

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36 Dimensions

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51 Mendeley
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Title
Technical considerations for genotyping multi-allelic copy number variation (CNV), in regions of segmental duplication
Published in
BMC Genomics, May 2014
DOI 10.1186/1471-2164-15-329
Pubmed ID
Authors

Stuart Cantsilieris, Patrick S Western, Paul N Baird, Stefan J White

Abstract

Intrachromosomal segmental duplications provide the substrate for non-allelic homologous recombination, facilitating extensive copy number variation in the human genome. Many multi-copy gene families are embedded within genomic regions with high levels of sequence identity (>95%) and therefore pose considerable analytical challenges. In some cases, the complexity involved in analyzing such regions is largely underestimated. Rapid, cost effective analysis of multi-copy gene regions have typically implemented quantitative approaches, however quantitative data are not an absolute means of certainty. Therefore any technique prone to degrees of measurement error can produce ambiguous results that may lead to spurious associations with complex disease.

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X Demographics

The data shown below were collected from the profiles of 2 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 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
Chile 1 2%
Hong Kong 1 2%
Sweden 1 2%
Unknown 47 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 22%
Student > Master 8 16%
Student > Bachelor 8 16%
Student > Doctoral Student 6 12%
Researcher 6 12%
Other 9 18%
Unknown 3 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 14 27%
Biochemistry, Genetics and Molecular Biology 10 20%
Medicine and Dentistry 9 18%
Pharmacology, Toxicology and Pharmaceutical Science 2 4%
Mathematics 2 4%
Other 8 16%
Unknown 6 12%
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 03 February 2015.
All research outputs
#16,720,137
of 25,371,288 outputs
Outputs from BMC Genomics
#6,569
of 11,244 outputs
Outputs of similar age
#140,067
of 242,173 outputs
Outputs of similar age from BMC Genomics
#137
of 248 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 36th percentile – i.e., 36% 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 242,173 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 248 others from the same source and published within six weeks on either side of this one. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.