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The combined model performed using miR-30e* as a dichotomous variable is shown in Table 1.
The associations between genotypes and hypersensitivity were analyzed using logistic regression model performed using SAS 9.1.3 software (SAS Institute, Cary, NC).
The branch model performed using a gene-tree reconstructed after excluding A. arabiensis and A. quadriannulatus from the dataset also detected episodic selection for the branch separating A. gambiae from the other two species (ω = 2.14; p < 0.05).
To account for genetic relatedness among individuals, the same marker data set used for population structure (Q matrix, fix effect) was also employed to generate a kinship matrix (K matrix), considered as random factor in the Mixed Linear Model performed using TASSEL [ 43, 44].
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The performance of the device has been analysed and compared to modelling performed using DeltaEC simulation tool.
Chronological age was included as a covariate in the Analysis of Variance (ANOVA) models performed using Proc GLM in SAS.
Multilevel modelling, performed using MLwiN (version 2.23) [ 22], was used to test for ethnic differences in activity.
Empirical evaluation and comparison of different models were performed using model selection criteria and goodness-of-fit statistics.
The Q model was performed using general linear model (GLM).
The validation of the model was performed using the "V-model" development process [16].
Simulation models were performed using Python 2.6.6 with NumPy 1.5.1rc2 and SciPy 0.8.0.
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