Sentence examples for mean trait data from inspiring English sources

Pearson's correlation coefficient analysis of mean trait data revealed several significant correlations.

Mean trait anxiety scores were higher than general population data (t = 4.9, n = 1059, P < 0.001) but not significantly different from published data from other screening samples.

When trait variation is scaled by the mean trait value, e.g. by log-transforming the data, the resulting log-transformed variance quantifies the variation that does not depend on the scale effect [ 13, 14].

For the DH population, the mean trait values and GCA effect were used as input data.

The trait data were treated as adjusted entry means (best linear unbiased predictors).

For example, with n = 50, the data correspond to a rather small change in mean trait values.

The population trait data presented in Figures 1a and b are the mean line values as used for QTL mapping for the KB, NG, SG and TJ populations.

Integrative sparse k-means clustering was performed using 1) Dura gene expression and PF trait data (Dura-Cranial), 2) Blood gene expression and PF trait data (Blood-Cranial), and 3) Blood gene expression, dura gene expression, and PF trait data (Blood-Dura-Cranial).

For each of the BC populations, the mean trait values and SCA effect of the BC hybrids were used as input data.

The heritability of gene expression means it can be subject to the same quantitative trait loci (QTL) analyses as conventional trait data to reveal the so-called expression QTLs (eQTLs).

Before investigating trait-metabolite correlations we removed the covariance between the trait data and the population membership Q-matrix from the STRUCTURE program by means of multiple linear regression.