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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A population model for genotyping indels from next-generation sequence data
|
|---|---|
| Published in |
Nucleic Acids Research, December 2012
|
| DOI | 10.1093/nar/gks1143 |
| Pubmed ID | |
| Authors |
Haojing Shao, Evangelos Bellos, Hanjiudai Yin, Xiao Liu, Jing Zou, Yingrui Li, Jun Wang, Lachlan J. M. Coin |
| Abstract |
Insertion and deletion polymorphisms (indels) are an important source of genomic variation in plant and animal genomes, but accurate genotyping from low-coverage and exome next-generation sequence data remains challenging. We introduce an efficient population clustering algorithm for diploids and polyploids which was tested on a dataset of 2000 exomes. Compared with existing methods, we report a 4-fold reduction in overall indel genotype error rates with a 9-fold reduction in low coverage regions. |
X Demographics
The data shown below were collected from the profiles of 22 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 Kingdom | 5 | 23% |
| United States | 3 | 14% |
| Germany | 2 | 9% |
| Canada | 2 | 9% |
| Sweden | 1 | 5% |
| Norway | 1 | 5% |
| Peru | 1 | 5% |
| Unknown | 7 | 32% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 15 | 68% |
| Members of the public | 6 | 27% |
| Science communicators (journalists, bloggers, editors) | 1 | 5% |
Mendeley readers
The data shown below were compiled from readership statistics for 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 5 | 7% |
| Sweden | 2 | 3% |
| Netherlands | 1 | 1% |
| Unknown | 60 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 20 | 29% |
| Student > Ph. D. Student | 14 | 21% |
| Student > Master | 6 | 9% |
| Other | 5 | 7% |
| Student > Postgraduate | 5 | 7% |
| Other | 13 | 19% |
| Unknown | 5 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 40 | 59% |
| Biochemistry, Genetics and Molecular Biology | 8 | 12% |
| Computer Science | 5 | 7% |
| Medicine and Dentistry | 4 | 6% |
| Mathematics | 1 | 1% |
| Other | 3 | 4% |
| Unknown | 7 | 10% |
Attention Score in Context
This research output has an Altmetric Attention Score of 23. 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 16 November 2015.
All research outputs
#1,620,147
of 25,373,627 outputs
Outputs from Nucleic Acids Research
#1,287
of 27,550 outputs
Outputs of similar age
#13,669
of 286,257 outputs
Outputs of similar age from Nucleic Acids Research
#11
of 367 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 27,550 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.1. This one has done particularly well, scoring higher than 95% 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 286,257 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 367 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 97% of its contemporaries.