We simulated single-generation data for a fitness trait in @entity409 ( @entity409 ) experiments, and we compared three methods of analysis. Bateman-Mukai (BM) and maximum likelihood (ML) need information on both the @entity409 lines and control lines, while @entity5529 ( @entity5529 ) can be applied with or without the control. Both @entity5529 and ML assume gamma-distributed mutational effects. ML estimates of the rate of deleterious mutation had larger @entity2246 ( @entity2246 ) than @entity5529 or BM had due to large outliers. @entity5529 estimates obtained by ignoring the mean decline observed from comparison to a control are often better than those obtained using that information. When effects are simulated using the gamma distribution, reducing the precision with which the trait is assayed increases the probability of obtaining no ML or @entity5529 estimates but causes no appreciable increase of the @entity2246 . When the residual errors for the means of the simulated lines are sampled from the empirical distribution in a @entity409 experiment, instead of from a normal one, the MSEs of BM, ML, and @entity5529 are practically unaffected. When the simulated gamma distribution accounts for a high rate of mild deleterious mutation, BM detects only approximately 30% of the true deleterious mutation rate, while @entity5529 or ML detects substantially larger fractions. To test the robustness of the methods, we also added a high rate of common contaminant mutations with constant mild deleterious effect to a low rate of mutations with gamma-distributed deleterious effects and moderate average. In that case, BM detects roughly the same fraction as before, regardless of the precision of the assay, while ML fails to provide estimates. However, @entity5529 estimates are obtained by ignoring the control information, detecting approximately 70% of the total mutation rate when the mean of the lines is assayed with good precision, but only 15% for low-precision assays. Contaminant mutations with only tiny deleterious effects could not be detected with acceptable accuracy by any of the above methods.

Comparing analysis methods for XXXX data: a simulation study.

@entity409 :: ('MESH:D008107', 'Disease') :: ['MA', 'mutation-accumulation'] @entity5529 :: ('MESH:C535290', 'Disease') :: ['MD', 'minimum distance'] @entity2246 :: ('MESH:D008661', 'Disease') :: ['MSE', 'mean square error']
@entity409 :: (MESH:D008107,Disease) :: ['mutation-accumulation']
