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Mendeley readers
Attention Score in Context
| Title |
Correcting for Population Stratification Reduces False Positive and False Negative Results in Joint Analyses of Host and Pathogen Genomes
|
|---|---|
| Published in |
Frontiers in Genetics, July 2018
|
| DOI | 10.3389/fgene.2018.00266 |
| Pubmed ID | |
| Authors |
Olivier Naret, Nimisha Chaturvedi, Istvan Bartha, Christian Hammer, Jacques Fellay, The Swiss HIV Cohort Study |
| Abstract |
Studies of host genetic determinants of pathogen sequence variations can identify sites of genomic conflicts, by highlighting variants that are implicated in immune response on the host side and adaptive escape on the pathogen side. However, systematic genetic differences in host and pathogen populations can lead to inflated type I (false positive) and type II (false negative) error rates in genome-wide association analyses. Here, we demonstrate through a simulation that correcting for both host and pathogen stratification reduces spurious signals and increases power to detect real associations in a variety of tested scenarios. We confirm the validity of the simulations by showing comparable results in an analysis of paired human and HIV genomes. |
X Demographics
The data shown below were collected from the profiles of 13 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 5 | 38% |
| United States | 2 | 15% |
| France | 1 | 8% |
| Unknown | 5 | 38% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 7 | 54% |
| Members of the public | 6 | 46% |
Mendeley readers
The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 22 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 23% |
| Researcher | 4 | 18% |
| Student > Master | 2 | 9% |
| Professor | 1 | 5% |
| Student > Doctoral Student | 1 | 5% |
| Other | 2 | 9% |
| Unknown | 7 | 32% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 6 | 27% |
| Biochemistry, Genetics and Molecular Biology | 4 | 18% |
| Engineering | 2 | 9% |
| Medicine and Dentistry | 2 | 9% |
| Psychology | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 7 | 32% |
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 19 August 2018.
All research outputs
#3,152,133
of 23,098,660 outputs
Outputs from Frontiers in Genetics
#925
of 12,152 outputs
Outputs of similar age
#64,662
of 329,967 outputs
Outputs of similar age from Frontiers in Genetics
#27
of 162 outputs
Altmetric has tracked 23,098,660 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 12,152 research outputs from this source. They receive a mean Attention Score of 3.7. This one has done particularly well, scoring higher than 92% 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 329,967 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 80% of its contemporaries.
We're also able to compare this research output to 162 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.