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On statistical modeling of sequencing noise in high depth data to assess tumor evolution
Raul Rabadan, Gyan Bhanot, Sonia Marsilio, Nicholas Chiorazzi, Laura Pasqualucci, View ORCID ProfileHossein Khiabanian
doi: https://doi.org/10.1101/128587
Raul Rabadan
1Department of Systems Biology, Columbia University, New York, NY
2Center for Topology of Cancer Evolution and Heterogeneity, Columbia University, New York, NY
Gyan Bhanot
3Department of Physics and Astronomy, Rutgers University, Piscataway, NJ
Sonia Marsilio
4The Feinstein Institute for Medical Research, Northwell Health, Manhasset, NY
Nicholas Chiorazzi
4The Feinstein Institute for Medical Research, Northwell Health, Manhasset, NY
Laura Pasqualucci
5Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, NJ
Hossein Khiabanian
2Center for Topology of Cancer Evolution and Heterogeneity, Columbia University, New York, NY

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Posted September 04, 2017.
On statistical modeling of sequencing noise in high depth data to assess tumor evolution
Raul Rabadan, Gyan Bhanot, Sonia Marsilio, Nicholas Chiorazzi, Laura Pasqualucci, Hossein Khiabanian
bioRxiv 128587; doi: https://doi.org/10.1101/128587
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