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Genetic covariances were estimated using a multi-trait animal model, assuming traits to be normally distributed.
However, the Q-method implicitly assumes traits are uncorrelated and hence underestimates the clustered pattern of spurious eQTL for correlated traits.
This implementation is based on simulation studies that assumed traits to be normally distributed with equal genotypic variances for each of the multi-locus genotype combinations corresponding to a bi-allelic functional SNP pair [ 6, 29].
Assuming traits are conditional dependence on associated genetic variations, Y i are independent of each other following a Gaussian distribution, as shown in the example illustrated by Fig. 1; hence, we assume Y can be divided into M clusters based on values of the quantitative trait.
SNP effects were estimated with a BLUP model assuming trait-specific residual polygenic variance (for more details on the model see [ 3]).
The continuous-time Markov character model assumes trait states can evolve repeatedly between their possible states at any branch of the phylogenetic tree [ 55, 56] and constructs the ancestral trait at each internal node.
They wrongly assume that traits can be determined from a single type of behavior stereotypically associated with that trait.
Assume two traits, Y and Y ′, have been measured in distinct samples and evidence exists for association of both traits to some genetic region.
Whenever you assume negative traits for a whole class of people, you are immediately at risk of losing them - losing the valuable contributions they could make to your team and to your bottom line.
Our inheritance design facilitates modeling genetics without having to assume that traits are normally distributed.
Classical QTL mapping methods assume that traits follow a normal distribution [ 48].
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com