Non-coding cancer driver candidates identified with a sample- and position-specific model of the somatic mutation rate

Non-coding cancer driver candidates identified with a sample- and position-specific model of the somatic mutation rate

Non-coding mutations may drive cancer development. Statistical detection of non-coding driver regions is challenged by a varying mutation rate and uncertainty of functional impact. Here, we develop a statistically founded non-coding driver-detection method, ncdDetect, which includes sample-specific...

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Bibliographic Details
Main Authors: Malene Juul, Johanna Bertl, Qianyun Guo, Morten Muhlig Nielsen, Michał Świtnicki, Henrik Hornshøj, Tobias Madsen, Asger Hobolth, Jakob Skou Pedersen
Format: Article
Language:English
Published: eLife Sciences Publications Ltd 2017-03-01
Series:eLife
Subjects:
cancer
driver detection
non-coding mutations
mutational processes
Online Access:https://elifesciences.org/articles/21778

Internet

https://elifesciences.org/articles/21778

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