Title |
A computational tool to detect DNA alterations tailored to formalin-fixed paraffin-embedded samples in cancer clinical sequencing
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Published in |
Genome Medicine, June 2018
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DOI | 10.1186/s13073-018-0547-0 |
Pubmed ID | |
Authors |
Mamoru Kato, Hiromi Nakamura, Momoko Nagai, Takashi Kubo, Asmaa Elzawahry, Yasushi Totoki, Yuko Tanabe, Eisaku Furukawa, Joe Miyamoto, Hiromi Sakamoto, Shingo Matsumoto, Kuniko Sunami, Yasuhito Arai, Yutaka Suzuki, Teruhiko Yoshida, Katsuya Tsuchihara, Kenji Tamura, Noboru Yamamoto, Hitoshi Ichikawa, Takashi Kohno, Tatsuhiro Shibata |
Abstract |
Advanced cancer genomics technologies are now being employed in clinical sequencing, where next-generation sequencers are used to simultaneously identify multiple types of DNA alterations for prescription of molecularly targeted drugs. However, no computational tool is available to accurately detect DNA alterations in formalin-fixed paraffin-embedded (FFPE) samples commonly used in hospitals. Here, we developed a computational tool tailored to the detection of single nucleotide variations, indels, fusions, and copy number alterations in FFPE samples. Elaborated multilayer noise filters reduced the inherent noise while maintaining high sensitivity, as evaluated in tumor-unmatched normal samples using orthogonal technologies. This tool, cisCall, should facilitate clinical sequencing in everyday diagnostics. It is available at https://www.ciscall.org . |
X Demographics
Geographical breakdown
Country | Count | As % |
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France | 1 | 33% |
United Kingdom | 1 | 33% |
Unknown | 1 | 33% |
Demographic breakdown
Type | Count | As % |
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Scientists | 2 | 67% |
Members of the public | 1 | 33% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 49 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 13 | 27% |
Student > Master | 10 | 20% |
Student > Ph. D. Student | 9 | 18% |
Other | 3 | 6% |
Lecturer | 2 | 4% |
Other | 4 | 8% |
Unknown | 8 | 16% |
Readers by discipline | Count | As % |
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Biochemistry, Genetics and Molecular Biology | 12 | 24% |
Agricultural and Biological Sciences | 11 | 22% |
Computer Science | 5 | 10% |
Medicine and Dentistry | 4 | 8% |
Social Sciences | 2 | 4% |
Other | 6 | 12% |
Unknown | 9 | 18% |