Small molecule profiling identifies shared and distinct pathways to non-communicable disease multimorbidity. Pietzner et al., 2020.
Results from linar regression models for clinical risk factors
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About this matrix
This matrix shows p-values, beta estimates and variance explained from linear regression models using >50 diverse baseline characteristics as the exposure and plasma levels of metabolites as the outcome, adjusted for age and sex.
You can filter/subset the matrix based on statistical criteria, such as association strength or effect estimates, or restricted to an exposure or outcome of interest using the "Settings" menu.
Metabolite name and superpathway (abbrv.)
Trait name and group (abbrv.)
Association between metabolite and traits.
Color: effect size and direction, ranging from -1 (blue) to +1 (red).
Bar: variance explained by trait, ranging from 0% to 25+%.
To sort associations, click on a row or column label.