↓ Skip to main content

The SSV Evaluation System: A Tool to Prioritize Short Structural Variants for Studies of Possible Regulatory and Causal Variants

Overview of attention for article published in Human Mutation, June 2016
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (60th percentile)

Mentioned by

news
1 news outlet
twitter
1 X user

Citations

dimensions_citation
15 Dimensions

Readers on

mendeley
16 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
The SSV Evaluation System: A Tool to Prioritize Short Structural Variants for Studies of Possible Regulatory and Causal Variants
Published in
Human Mutation, June 2016
DOI 10.1002/humu.23023
Pubmed ID
Authors

Robert Saul, Michael W Lutz, Daniel K Burns, Allen D Roses, Ornit Chiba-Falek

Abstract

Short structural variants (SSVs) are short genomic variants (<50 bp) other than SNPs. It has been suggested that SSVs contribute to many human complex traits. However, high-throughput analysis of SSVs presents numerous technical challenges. In order to facilitate the discovery and assessment of SSVs, we have developed a prototype bioinformatics tool, "SSV evaluation system," which is a searchable, annotated database of SSVs in the human genome, with associated customizable scoring software that is used to evaluate and prioritize SSVs that are most likely to have significant biological effects and impact on disease risk. This new bioinformatics tool is a component in a larger strategy that we have been using to discover potentially important SSVs within candidate genomic regions that have been identified in genome-wide association studies, with the goal to prioritize potential functional/causal SSVs and focus the follow-up experiments on a relatively small list of strong candidate SSVs. We describe our strategy and discuss how we have used the SSV evaluation system to discover candidate causal variants related to complex neurodegenerative diseases. We present the SSV evaluation system as a powerful tool to guide genetic investigations aiming to uncover SSVs that underlie human complex diseases including neurodegenerative diseases in aging.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 31%
Student > Ph. D. Student 3 19%
Lecturer > Senior Lecturer 1 6%
Student > Bachelor 1 6%
Other 1 6%
Other 2 13%
Unknown 3 19%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 25%
Medicine and Dentistry 3 19%
Agricultural and Biological Sciences 2 13%
Neuroscience 2 13%
Computer Science 1 6%
Other 0 0%
Unknown 4 25%
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 18 December 2017.
All research outputs
#3,709,974
of 25,373,627 outputs
Outputs from Human Mutation
#289
of 2,982 outputs
Outputs of similar age
#63,827
of 367,717 outputs
Outputs of similar age from Human Mutation
#8
of 23 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 2,982 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done particularly well, scoring higher than 90% 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 367,717 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 82% of its contemporaries.
We're also able to compare this research output to 23 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 60% of its contemporaries.