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The UNIFRAC metric measures the distance between communities as the percentage of branch length that leads to descendants from only one of a pair of environments represented in a single phylogenetic tree, i.e. the fraction of evolution that is unique to one of the microbial communities.
Slope was calculated using the standardized phenotype values for each pair of environments.
When 3 min are given, the transition of trade-offs from weak to strong occurs at a much more similar pair of environments.
Results of the mixed model analysis that estimate unique genotypic covariances for each pair of environments indicated that the two Galicia environments had a much stronger genotypic correlation (r = 0.93; Table 1 and Figure S2) than did any other pair of environments (range, r = 0.28 to 0.51; Table 1 and Figure S2).
Estimates of genotypic covariance from the mixed model analysis for each trait and for each pair of environments showed that the two Manhattan environments had a much stronger genotypic correlation for all parameters (Table 2) than did any other pair of environments.
The ith genetic correlation was from the same pair of environments for both models and n was equal to six, because with four environments there are six genetic correlations.
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This mapping identified alleles that acted antagonistically across pairs of environments.
Figures 10a-c are scatter plots based on 1000 random genotypes viable in pairs of environments.
To identify QTL contributing to plasticity across pairs of environments, gene environment interaction mapping was performed, which identified several QTL that have a differential effect across environments, some of which act antagonistically across pairs of environments.
The interaction model can be applied to all available environments or to other sets (e.g., pairs) of environments.
GEI mapping was performed to identify small-effect QTL that contributed to growth plasticity across pairs of environments.
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