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At the end, the mutation score is calculated, given by the number of generated and dead mutants.
The mutation score is a value in the interval [0,1] that reflects the quality of the test set with respect to the produced mutants.
The mutation score is used only in the work of Henard et al. (2014), which implements the (1+1) Evolutionary Algorithm (EA) algorithm, and considers the operators defined in (Henard et al. 2013a).
The mutation score is used by the software to call a mutation and rank its confidence level.
Mutation score is similar to that of ROSETTA, as shown in Equation (1), which is to compute the similarity score between profiles.
Due to the nature of sequencing, however, peak heights may be quite variable so it is important that both directions are examined when the mutation score is used as an indication of the zygosity.
Similar(51)
The percentages of subjects that had at least one mutation listed in the TPV mutation score were not significantly different in both groups (11/21 vs. 15/20, P = 0.197).
The TPV mutation score was not significantly different between the subjects with RTV-boosted ATV and the subjects with ATV without RTV.
Consequently, the isolated DNA employed for mutation scoring is mainly from hepatocytes, and not fibroblast contamination.
Afterwards, the means of the mutation scores are obtained and compared.
The effect sizes for germline mutation scores are mostly ∼50% of the expectation under the null.
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