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Mendeley readers
| Title |
CNAReporter: a GenePattern pipeline for the generation of clinical reports of genomic alterations
|
|---|---|
| Published in |
BMC Medical Genomics, April 2010
|
| DOI | 10.1186/1755-8794-3-11 |
| Pubmed ID | |
| Authors |
Yuri Kotliarov, Serdar Bozdag, Hangjiong Cheng, Stefan Wuchty, Jean-Claude Zenklusen, Howard A Fine |
| Abstract |
Genomic copy number alterations are widely associated with a broad range of human tumors and offer the potential to be used as a diagnostic tool. Especially in the emerging era of personalized medicine medical informatics tools that allow the fast visualization and analysis of genomic alterations of a patient's genomic profile for diagnostic and potential treatment purposes increasingly gain importance. We developed CNAReporter, a software tool that allows users to visualize SNP-specific data obtained from Affymetrix arrays and generate PDF-reports as output. We combined standard algorithms for the analysis of chromosomal alterations, utilizing the widely applied GenePattern framework. As an example, we show genome analyses of two patients with distinctly different CNA profiles using the tool. Glioma subtypes, characterized by different genomic alterations, are often treated differently but can be difficult to differentiate pathologically. CNAReporter offers a user-friendly way to visualize and analyse genomic changes of any given tumor genomic profile, thereby leading to an accurate diagnosis and patient-specific treatment. |
Mendeley readers
The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 3% |
| Brazil | 1 | 3% |
| Unknown | 28 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 7 | 23% |
| Professor | 5 | 17% |
| Student > Bachelor | 4 | 13% |
| Student > Ph. D. Student | 4 | 13% |
| Other | 3 | 10% |
| Other | 6 | 20% |
| Unknown | 1 | 3% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 11 | 37% |
| Medicine and Dentistry | 6 | 20% |
| Computer Science | 5 | 17% |
| Engineering | 3 | 10% |
| Biochemistry, Genetics and Molecular Biology | 2 | 7% |
| Other | 1 | 3% |
| Unknown | 2 | 7% |