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dbVOR: a database system for importing pedigree, phenotype and genotype data and exporting selected subsets

Overview of attention for article published in BMC Bioinformatics, March 2015
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  • Above-average Attention Score compared to outputs of the same age (51st percentile)
  • Average Attention Score compared to outputs of the same age and source

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Title
dbVOR: a database system for importing pedigree, phenotype and genotype data and exporting selected subsets
Published in
BMC Bioinformatics, March 2015
DOI 10.1186/s12859-015-0505-4
Pubmed ID
Authors

Robert V Baron, Yvette P Conley, Michael B Gorin, Daniel E Weeks

Abstract

When studying the genetics of a human trait, we typically have to manage both genome-wide and targeted genotype data. There can be overlap of both people and markers from different genotyping experiments; the overlap can introduce several kinds of problems. Most times the overlapping genotypes are the same, but sometimes they are different. Occasionally, the lab will return genotypes using a different allele labeling scheme (for example 1/2 vs A/C). Sometimes, the genotype for a person/marker index is unreliable or missing. Further, over time some markers are merged and bad samples are re-run under a different sample name. We need a consistent picture of the subset of data we have chosen to work with even though there might possibly be conflicting measurements from multiple data sources. We have developed the dbVOR database, which is designed to hold data efficiently for both genome-wide and targeted experiments. The data are indexed for fast retrieval by person and marker. In addition, we store pedigree and phenotype data for our subjects. The dbVOR database allows us to select subsets of the data by several different criteria and to merge their results into a coherent and consistent whole. Data may be filtered by: family, person, trait value, markers, chromosomes, and chromosome ranges. The results can be presented in columnar, Mega2, or PLINK format. dbVOR serves our needs well. It is freely available from https://watson.hgen.pitt.edu/register . Documentation for dbVOR can be found at https://watson.hgen.pitt.edu/register/docs/dbvor.html .

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Sweden 1 4%
France 1 4%
Unknown 21 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 43%
Student > Postgraduate 4 17%
Student > Bachelor 3 13%
Professor 2 9%
Student > Ph. D. Student 1 4%
Other 2 9%
Unknown 1 4%
Readers by discipline Count As %
Agricultural and Biological Sciences 10 43%
Biochemistry, Genetics and Molecular Biology 7 30%
Computer Science 3 13%
Medicine and Dentistry 2 9%
Unknown 1 4%
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 26 November 2015.
All research outputs
#14,053,782
of 24,226,848 outputs
Outputs from BMC Bioinformatics
#4,095
of 7,512 outputs
Outputs of similar age
#138,414
of 290,670 outputs
Outputs of similar age from BMC Bioinformatics
#78
of 138 outputs
Altmetric has tracked 24,226,848 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,512 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 45th percentile – i.e., 45% 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 290,670 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 51% of its contemporaries.
We're also able to compare this research output to 138 others from the same source and published within six weeks on either side of this one. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.