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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.

SUBMITTER: Kim SY 

PROVIDER: S-EPMC4035752 | biostudies-literature | 2014 May

REPOSITORIES: biostudies-literature

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Publications

Combining calls from multiple somatic mutation-callers.

Kim Su Yeon SY   Jacob Laurent L   Speed Terence P TP  

BMC bioinformatics 20140521


<h4>Background</h4>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.<h4>Results</h4>Using a set of mutati  ...[more]

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