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Mendeley readers
Attention Score in Context
Title |
BCRgt: a Bayesian cluster regression-based genotyping algorithm for the samples with copy number alterations
|
---|---|
Published in |
BMC Bioinformatics, March 2014
|
DOI | 10.1186/1471-2105-15-74 |
Pubmed ID | |
Authors |
Shengping Yang, Xiangqin Cui, Zhide Fang |
Abstract |
Accurate genotype calling is a pre-requisite of a successful Genome-Wide Association Study (GWAS). Although most genotyping algorithms can achieve an accuracy rate greater than 99% for genotyping DNA samples without copy number alterations (CNAs), almost all of these algorithms are not designed for genotyping tumor samples that are known to have large regions of CNAs. |
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.
Geographical breakdown
Country | Count | As % |
---|---|---|
Norway | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 11 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Bachelor | 2 | 18% |
Student > Postgraduate | 2 | 18% |
Other | 1 | 9% |
Student > Ph. D. Student | 1 | 9% |
Lecturer | 1 | 9% |
Other | 2 | 18% |
Unknown | 2 | 18% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 4 | 36% |
Computer Science | 4 | 36% |
Biochemistry, Genetics and Molecular Biology | 1 | 9% |
Unknown | 2 | 18% |
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 16 March 2014.
All research outputs
#20,224,618
of 22,749,166 outputs
Outputs from BMC Bioinformatics
#6,840
of 7,268 outputs
Outputs of similar age
#189,771
of 221,158 outputs
Outputs of similar age from BMC Bioinformatics
#90
of 100 outputs
Altmetric has tracked 22,749,166 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,268 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 1st percentile – i.e., 1% 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 221,158 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 100 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.