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- W2064152621 abstract "Accurate somatic mutation-calling is essential for insightful mutation analyses in cancer studies. Several mutation-callers are publicly available and more are likely to appear. Nonetheless, mutation-calling is still challenging and there is unlikely to be one established caller that systematically outperforms all others. Therefore, fully utilizing multiple callers can be a powerful way to construct a list of final calls for one’s research. Using a set of mutations from multiple callers that are impartially validated, we present a statistical approach for building a combined caller, which can be applied to combine calls in a wider dataset generated using a similar protocol. Using the mutation outputs and the validation data from The Cancer Genome Atlas endometrial study (6,746 sites), we demonstrate how to build a statistical model that predicts the probability of each call being a somatic mutation, based on the detection status of multiple callers and a few associated features. The approach allows us to build a combined caller across the full range of stringency levels, which outperforms all of the individual callers." @default.
- W2064152621 created "2016-06-24" @default.
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- W2064152621 date "2014-05-21" @default.
- W2064152621 modified "2023-10-10" @default.
- W2064152621 title "Combining calls from multiple somatic mutation-callers" @default.
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- W2064152621 doi "https://doi.org/10.1186/1471-2105-15-154" @default.
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