| Title |
Hybridization and amplification rate correction for affymetrix SNP arrays
|
|---|---|
| Published in |
BMC Medical Genomics, June 2012
|
| DOI | 10.1186/1755-8794-5-24 |
| Pubmed ID | |
| Authors |
Quan Wang, Peichao Peng, Minping Qian, Lin Wan, Minghua Deng |
| Abstract |
Copy number variation (CNV) is essential to understand the pathology of many complex diseases at the DNA level. Affymetrix SNP arrays, which are widely used for CNV studies, significantly depend on accurate copy number (CN) estimation. Nevertheless, CN estimation may be biased by several factors, including cross-hybridization and training sample batch, as well as genomic waves of intensities induced by sequence-dependent hybridization rate and amplification efficiency. Since many available algorithms only address one or two of the three factors, a high false discovery rate (FDR) often results when identifying CNV. Therefore, we have developed a new CNV detection pipeline which is based on hybridization and amplification rate correction (CNVhac). |
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 Kingdom | 1 | 50% |
| United States | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Sweden | 1 | 5% |
| Unknown | 19 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 25% |
| Researcher | 4 | 20% |
| Student > Master | 3 | 15% |
| Student > Postgraduate | 2 | 10% |
| Professor | 1 | 5% |
| Other | 3 | 15% |
| Unknown | 2 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 5 | 25% |
| Medicine and Dentistry | 5 | 25% |
| Biochemistry, Genetics and Molecular Biology | 2 | 10% |
| Unspecified | 1 | 5% |
| Earth and Planetary Sciences | 1 | 5% |
| Other | 3 | 15% |
| Unknown | 3 | 15% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 06 July 2012.
All research outputs
#16,722,190
of 25,374,917 outputs
Outputs from BMC Medical Genomics
#1,194
of 2,444 outputs
Outputs of similar age
#115,659
of 180,999 outputs
Outputs of similar age from BMC Medical Genomics
#17
of 35 outputs
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So far Altmetric has tracked 2,444 research outputs from this source. They receive a mean Attention Score of 4.4. This one is in the 46th percentile – i.e., 46% of its peers scored the same or lower than it.
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We're also able to compare this research output to 35 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.