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X Demographics
Mendeley readers
Attention Score in Context
| Title |
SeqCNV: a novel method for identification of copy number variations in targeted next-generation sequencing data
|
|---|---|
| Published in |
BMC Bioinformatics, March 2017
|
| DOI | 10.1186/s12859-017-1566-3 |
| Pubmed ID | |
| Authors |
Yong Chen, Li Zhao, Yi Wang, Ming Cao, Violet Gelowani, Mingchu Xu, Smriti A. Agrawal, Yumei Li, Stephen P. Daiger, Richard Gibbs, Fei Wang, Rui Chen |
| Abstract |
Targeted next-generation sequencing (NGS) has been widely used as a cost-effective way to identify the genetic basis of human disorders. Copy number variations (CNVs) contribute significantly to human genomic variability, some of which can lead to disease. However, effective detection of CNVs from targeted capture sequencing data remains challenging. Here we present SeqCNV, a novel CNV calling method designed to use capture NGS data. SeqCNV extracts the read depth information and utilizes the maximum penalized likelihood estimation (MPLE) model to identify the copy number ratio and CNV boundary. We applied SeqCNV to both bacterial artificial clone (BAC) and human patient NGS data to identify CNVs. These CNVs were validated by array comparative genomic hybridization (aCGH). SeqCNV is able to robustly identify CNVs of different size using capture NGS data. Compared with other CNV-calling methods, SeqCNV shows a significant improvement in both sensitivity and specificity. |
X Demographics
The data shown below were collected from the profiles of 11 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 States | 2 | 18% |
| Israel | 2 | 18% |
| United Kingdom | 2 | 18% |
| Russia | 1 | 9% |
| China | 1 | 9% |
| Germany | 1 | 9% |
| France | 1 | 9% |
| Unknown | 1 | 9% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 9 | 82% |
| Members of the public | 2 | 18% |
Mendeley readers
The data shown below were compiled from readership statistics for 131 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Italy | 1 | <1% |
| Brazil | 1 | <1% |
| Unknown | 129 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 32 | 24% |
| Student > Ph. D. Student | 24 | 18% |
| Student > Master | 16 | 12% |
| Student > Bachelor | 15 | 11% |
| Student > Doctoral Student | 6 | 5% |
| Other | 16 | 12% |
| Unknown | 22 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 49 | 37% |
| Agricultural and Biological Sciences | 28 | 21% |
| Computer Science | 10 | 8% |
| Medicine and Dentistry | 5 | 4% |
| Engineering | 4 | 3% |
| Other | 9 | 7% |
| Unknown | 26 | 20% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 22 March 2021.
All research outputs
#3,441,376
of 26,017,215 outputs
Outputs from BMC Bioinformatics
#1,102
of 7,793 outputs
Outputs of similar age
#60,138
of 327,964 outputs
Outputs of similar age from BMC Bioinformatics
#17
of 143 outputs
Altmetric has tracked 26,017,215 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 7,793 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. This one has done well, scoring higher than 85% 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 327,964 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 81% of its contemporaries.
We're also able to compare this research output to 143 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.