| Title |
Synthesis-View: visualization and interpretation of SNP association results for multi-cohort, multi-phenotype data and meta-analysis
|
|---|---|
| Published in |
BioData Mining, December 2010
|
| DOI | 10.1186/1756-0381-3-10 |
| Pubmed ID | |
| Authors |
Sarah A Pendergrass, Scott M Dudek, Dana C Crawford, Marylyn D Ritchie |
| Abstract |
Initial genome-wide association study (GWAS) discoveries are being further explored through the use of large cohorts across multiple and diverse populations involving meta-analyses within large consortia and networks. Many of the additional studies characterize less than 100 single nucleotide polymorphisms (SNPs), often include multiple and correlated phenotypic measurements, and can include data from multiple-sites, multiple-studies, as well as multiple race/ethnicities. New approaches for visualizing resultant data are necessary in order to fully interpret results and obtain a broad view of the trends between DNA variation and phenotypes, as well as provide information on specific SNP and phenotype relationships. |
Mendeley readers
The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 2 | 4% |
| United Kingdom | 1 | 2% |
| United States | 1 | 2% |
| Australia | 1 | 2% |
| Unknown | 45 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 22% |
| Researcher | 9 | 18% |
| Professor | 4 | 8% |
| Student > Doctoral Student | 3 | 6% |
| Student > Postgraduate | 3 | 6% |
| Other | 11 | 22% |
| Unknown | 9 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 14 | 28% |
| Medicine and Dentistry | 9 | 18% |
| Computer Science | 8 | 16% |
| Biochemistry, Genetics and Molecular Biology | 5 | 10% |
| Linguistics | 1 | 2% |
| Other | 5 | 10% |
| Unknown | 8 | 16% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 14 June 2011.
All research outputs
#5,718,233
of 22,709,015 outputs
Outputs from BioData Mining
#118
of 307 outputs
Outputs of similar age
#41,648
of 180,469 outputs
Outputs of similar age from BioData Mining
#1
of 2 outputs
Altmetric has tracked 22,709,015 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 307 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one has gotten more attention than average, scoring higher than 60% 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 180,469 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 76% of its contemporaries.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them