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Valection: design optimization for validation and verification studies.
- Author(s): Cooper, Christopher I;
- Yao, Delia;
- Sendorek, Dorota H;
- Yamaguchi, Takafumi N;
- P'ng, Christine;
- Houlahan, Kathleen E;
- Caloian, Cristian;
- Fraser, Michael;
- SMC-DNA Challenge Participants;
- Ellrott, Kyle;
- Margolin, Adam A;
- Bristow, Robert G;
- Stuart, Joshua M;
- Boutros, Paul C
- et al.
Published Web Locationhttps://doi.org/10.1186/s12859-018-2391-z
BackgroundPlatform-specific error profiles necessitate confirmatory studies where predictions made on data generated using one technology are additionally verified by processing the same samples on an orthogonal technology. However, verifying all predictions can be costly and redundant, and testing a subset of findings is often used to estimate the true error profile.
ResultsTo determine how to create subsets of predictions for validation that maximize accuracy of global error profile inference, we developed Valection, a software program that implements multiple strategies for the selection of verification candidates. We evaluated these selection strategies on one simulated and two experimental datasets.
ConclusionsValection is implemented in multiple programming languages, available at: http://labs.oicr.on.ca/boutros-lab/software/valection.
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