Sentence examples for associations we only from inspiring English sources

Since we were interested in causal direction for predetermined three-way associations, we only selected SNPs associated with both the methylation and expression levels in cis.

In an attempt to minimise the effect of chronic diseases and medications on immune-depression associations, we only included patients free of major chronic diseases and antidepressant use at the time of blood sampling in our sensitivity analysis.

Depression is a known risk factor for CVD 39; while our analyses adjust for depression diagnosis and suggest that it does not influence our observed associations, we only adjusted for baseline depression diagnosis and did not assess the potentially additional role of chronic depression.

While we did not find such an association, we only followed offspring to age 21.

To avoid confounding association, we only selected trauma patients and prospectively followed them to determine whether those who had genetic variants had a lesser or higher risk of post-traumatic MODS and sepsis.

For GenAge associations we used only mouse genes and mouse orthologs of human genes listed in GenAge.

In order to facilitate future analyses of the genotype-phenotype associations, we recruited only genetically unrelated individuals.

Among the top 66 associations, we identified only two other genes that were annotated by multiple haplotype tests showing evidence for an association at P<0.001.

While the linear model described earlier can be used to obtain positive or negative associations, we considered only negative associations because miRNAs act as negative regulators of their direct targets.

To avoid confounding associations, we selected only trauma patients and followed them prospectively to determine whether those who had genetic variants had a lesser or higher risk of posttraumatic MODS and sepsis.

To predict new GO term associations, we are only interested in values of probability equal to one because they correspond to the case of hard clustering, in which there is no overlap between clusters, and hence, there is no ambiguity in predicted GO term associations.