| Title |
SNVerGUI: a desktop tool for variant analysis of next-generation sequencing data
|
|---|---|
| Published in |
Journal of Medical Genetics, September 2012
|
| DOI | 10.1136/jmedgenet-2012-101001 |
| Pubmed ID | |
| Authors |
Wei Wang, Weicheng Hu, Fang Hou, Pingzhao Hu, Zhi Wei |
| Abstract |
Advances in next generation sequencing (NGS) technology have made it possible to interrogate comprehensively genome-wide genetic variations. However, most existing tools for variation detection are based on command-line interface, which discourages the main end users of NGS data, such as biologists, geneticists and clinicians, from utilising the software. |
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.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 50% |
| United Kingdom | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 5% |
| United Kingdom | 1 | 3% |
| Sweden | 1 | 3% |
| Canada | 1 | 3% |
| Unknown | 34 | 87% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 14 | 36% |
| Student > Ph. D. Student | 11 | 28% |
| Student > Bachelor | 4 | 10% |
| Professor | 3 | 8% |
| Other | 3 | 8% |
| Other | 4 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 15 | 38% |
| Computer Science | 7 | 18% |
| Medicine and Dentistry | 6 | 15% |
| Biochemistry, Genetics and Molecular Biology | 5 | 13% |
| Psychology | 1 | 3% |
| Other | 3 | 8% |
| Unknown | 2 | 5% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 25 October 2012.
All research outputs
#17,289,919
of 25,390,970 outputs
Outputs from Journal of Medical Genetics
#2,786
of 3,120 outputs
Outputs of similar age
#125,934
of 191,377 outputs
Outputs of similar age from Journal of Medical Genetics
#26
of 28 outputs
Altmetric has tracked 25,390,970 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,120 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one is in the 7th percentile – i.e., 7% 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 191,377 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 28 others from the same source and published within six weeks on either side of this one. This one is in the 7th percentile – i.e., 7% of its contemporaries scored the same or lower than it.