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- Title
Valection: design optimization for validation and verification studies.
- Authors
Cooper, Christopher I; Yao, Delia; Sendorek, Dorota H; Yamaguchi, Takafumi N; P'ng, Christine; Houlahan, Kathleen E; Caloian, Cristian; Fraser, Michael; Ellrott, Kyle; Margolin, Adam A; Bristow, Robert G; Stuart, Joshua M; Boutros, Paul C
- Abstract
Background: Platform-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. Results: To 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. Conclusions: Valection is implemented in multiple programming languages, available at: http://labs.oicr.on.ca/boutros-lab/software/valection
- Subjects
DNA data banks; NUCLEOTIDE sequencing; LOGICAL prediction; MEDICAL software; FALSE positive error
- Publication
BMC Bioinformatics, 2018, Vol 19, Issue 1, p1
- ISSN
1471-2105
- Publication type
Article
- DOI
10.1186/s12859-018-2391-z