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FamAgg: an R package to evaluate familial aggregation of traits in large pedigrees

Overview of attention for article published in Bioinformatics, January 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)
  • Average Attention Score compared to outputs of the same age and source

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Article details
Title
FamAgg: an R package to evaluate familial aggregation of traits in large pedigrees
Published in
Bioinformatics, January 2016
DOI 10.1093/bioinformatics/btw019
Pubmed ID
Authors
Abstract

Familial aggregation analysis is the first fundamental step to perform when assessing the extent of genetic background of a disease. However, there is a lack of software to analyze the familial clustering of complex phenotypes in very large pedigrees. Such pedigrees can be utilized to calculate measures that express trait aggregation on both the family and individual level, providing valuable directions in choosing families for detailed follow-up studies. We developed FamAgg, an open source R package that contains both established and novel methods to investigate familial aggregation of traits in large pedigrees. We demonstrate its use and interpretation by analyzing a publicly available cancer data set with more than 20,000 participants distributed across approximately 400 families. The FamAgg package is freely available at the Bioconductor repository, http://www.bioconductor.org/packages/FamAgg. [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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X Demographics

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 demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 31 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 8 26%
Student > Ph. D. Student 7 23%
Student > Master 5 16%
Professor > Associate Professor 2 6%
Student > Postgraduate 2 6%
Other 3 10%
Unknown 4 13%
Readers by discipline
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 11 35%
Agricultural and Biological Sciences 4 13%
Veterinary Science and Veterinary Medicine 2 6%
Computer Science 2 6%
Social Sciences 2 6%
Other 6 19%
Unknown 4 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 15 May 2016.
All research outputs
#3,561,374
of 25,373,627 outputs
Outputs from Bioinformatics
#3,087
of 12,808 outputs
Outputs of similar age
#59,195
of 403,895 outputs
Outputs of similar age from Bioinformatics
#105
of 177 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 12,808 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one has done well, scoring higher than 75% 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 403,895 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 177 others from the same source and published within six weeks on either side of this one. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.