| Title |
Comparison of methods to detect copy number alterations in cancer using simulated and real genotyping data
|
|---|---|
| Published in |
BMC Bioinformatics, August 2012
|
| DOI | 10.1186/1471-2105-13-192 |
| Pubmed ID | |
| Authors |
David Mosén-Ansorena, Ana María Aransay, Naiara Rodríguez-Ezpeleta |
| Abstract |
The detection of genomic copy number alterations (CNA) in cancer based on SNP arrays requires methods that take into account tumour specific factors such as normal cell contamination and tumour heterogeneity. A number of tools have been recently developed but their performance needs yet to be thoroughly assessed. To this aim, a comprehensive model that integrates the factors of normal cell contamination and intra-tumour heterogeneity and that can be translated to synthetic data on which to perform benchmarks is indispensable. |
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 % |
|---|---|---|
| Unknown | 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 76 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 5% |
| United Kingdom | 2 | 3% |
| Canada | 2 | 3% |
| France | 1 | 1% |
| Norway | 1 | 1% |
| Germany | 1 | 1% |
| Spain | 1 | 1% |
| Belgium | 1 | 1% |
| Unknown | 63 | 83% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 31 | 41% |
| Student > Ph. D. Student | 23 | 30% |
| Student > Bachelor | 5 | 7% |
| Student > Master | 5 | 7% |
| Other | 4 | 5% |
| Other | 5 | 7% |
| Unknown | 3 | 4% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 36 | 47% |
| Biochemistry, Genetics and Molecular Biology | 14 | 18% |
| Medicine and Dentistry | 10 | 13% |
| Computer Science | 5 | 7% |
| Engineering | 3 | 4% |
| Other | 5 | 7% |
| Unknown | 3 | 4% |
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 27 May 2014.
All research outputs
#14,771,194
of 22,739,983 outputs
Outputs from BMC Bioinformatics
#5,039
of 7,266 outputs
Outputs of similar age
#102,818
of 166,651 outputs
Outputs of similar age from BMC Bioinformatics
#61
of 103 outputs
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