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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
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Gyan Bhanot
3Department of Physics and Astronomy, Rutgers University, Piscataway, NJ
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Sonia Marsilio
4The Feinstein Institute for Medical Research, Northwell Health, Manhasset, NY
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Nicholas Chiorazzi
4The Feinstein Institute for Medical Research, Northwell Health, Manhasset, NY
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Laura Pasqualucci
5Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, NJ
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Hossein Khiabanian
2Center for Topology of Cancer Evolution and Heterogeneity, Columbia University, New York, NY
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  • ORCID record for Hossein Khiabanian
  • For correspondence: h.khiabanian@rutgers.edu
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Posted September 04, 2017.
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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, Hossein Khiabanian
bioRxiv 128587; doi: https://doi.org/10.1101/128587
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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, Hossein Khiabanian
bioRxiv 128587; doi: https://doi.org/10.1101/128587

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