Graphics Reference
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variables and an individual variable vector across all samples; (
)an association score
for every sample-sample and variable-variable relationship; (
) a grouping structure
for variables and a clustering effect for samples, and; (
) an interaction pattern for
sample clusters on variable groups.
With the capacity to display thousands of variables in a single picture, the flexi-
bility to work with all types of data, and the ability to handle various manifestations
of extraordinary data patterns (missing value, covariate adjustment), we believe that
matrix visualization hasthe potential tobecome oneofthe mostimportant graphical
tools applied to exploratory data analysis (EDA) in the future.
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