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Combining calls from multiple somatic mutation-callers

Abstract : Background: 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. Results: 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. Conclusion: The approach allows us to build a combined caller across the full range of stringency levels, which outperforms all of the individual callers.
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Contributor : Christelle Cheval Connect in order to contact the contributor
Submitted on : Friday, February 22, 2019 - 7:05:29 PM
Last modification on : Friday, March 4, 2022 - 3:21:38 PM

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S. Y. Kim, Laurent Jacob, T. P. Speed. Combining calls from multiple somatic mutation-callers. BMC Bioinformatics, BioMed Central, 2014, 15, pp.154. ⟨10.1186/1471-2105-15-154⟩. ⟨hal-02046830⟩



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