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These beads were removed from our variance calculations.
The comparable metric for our variance measurement was 91% (Additional File 1, Supplemental Methods 3).
This effectively regularizes our variance estimate in the case that the number of replicates is low.
These results are almost in complete agreement with our variance component analysis results when the GRM is fitted individually.
The likely effect would be to deflate genetic variance estimates, which would render our variance estimates conservative.
Our results show minimal enrichment for TAVs in miRNA target sites, with our variance component analysis showing no extra variance to be explained by this class.
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We are more interesting and nuanced as a culture and a society when we both recognize and value our variances and seek to include rather than exclude.
In terms of its conservation properties, our variance-conserving scheme is compared to other spatially variance-conserving schemes as well as with the non-variance-conserving schemes applied in our shallow-water solver, see e.g. [Direct and Large-eddy Simulation Workshop IV, ERCOFTAC Series, Kluwer Academic Publishers, 2001, pp. 409 287].
Stated differently, as given by our evidence, there is no severe multi-collinearity in the model that can affect our variances and co-variances which can also affect the precision of our estimation.
Since our variance-covariance matrices (indeed correlation matrices) have all diagonal elements equal to 1, we can incorporate λ into the matrix using this simple calculation: (8) Σ λ = λ Σ + (1 − λ ) I where I is the identity matrix.
A measurement of this property in real maps is in principle possible, and comparison with the results in our paper could help establish the role of our minimum variance hypothesis in the development process.
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