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Comparison of measures of marker informativeness for ancestry and admixture mapping

Overview of attention for article published in BMC Genomics, December 2011
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  • Above-average Attention Score compared to outputs of the same age and source (54th percentile)

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Title
Comparison of measures of marker informativeness for ancestry and admixture mapping
Published in
BMC Genomics, December 2011
DOI 10.1186/1471-2164-12-622
Pubmed ID
Authors

Lili Ding, Howard Wiener, Tilahun Abebe, Mekbib Altaye, Rodney CP Go, Carolyn Kercsmar, Greg Grabowski, Lisa J Martin, Gurjit K Khurana Hershey, Ranajit Chakorborty, Tesfaye M Baye

Abstract

Admixture mapping is a powerful gene mapping approach for an admixed population formed from ancestral populations with different allele frequencies. The power of this method relies on the ability of ancestry informative markers (AIMs) to infer ancestry along the chromosomes of admixed individuals. In this study, more than one million SNPs from HapMap databases and simulated data have been interrogated in admixed populations using various measures of ancestry informativeness: Fisher Information Content (FIC), Shannon Information Content (SIC), F statistics (FST), Informativeness for Assignment Measure (In), and the Absolute Allele Frequency Differences (delta, δ). The objectives are to compare these measures of informativeness to select SNP markers for ancestry inference, and to determine the accuracy of AIM panels selected by each measure in estimating the contributions of the ancestors to the admixed population.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 95 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
Brazil 2 2%
Netherlands 1 1%
France 1 1%
United Kingdom 1 1%
South Africa 1 1%
Unknown 87 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 23 24%
Student > Ph. D. Student 16 17%
Student > Bachelor 13 14%
Student > Master 11 12%
Professor > Associate Professor 4 4%
Other 11 12%
Unknown 17 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 40 42%
Biochemistry, Genetics and Molecular Biology 17 18%
Medicine and Dentistry 6 6%
Social Sciences 3 3%
Chemistry 2 2%
Other 5 5%
Unknown 22 23%
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 17 March 2016.
All research outputs
#12,852,228
of 22,660,862 outputs
Outputs from BMC Genomics
#4,547
of 10,610 outputs
Outputs of similar age
#142,669
of 243,104 outputs
Outputs of similar age from BMC Genomics
#130
of 296 outputs
Altmetric has tracked 22,660,862 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,610 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 55% 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 243,104 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 296 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 54% of its contemporaries.