swamp: Visualization, Analysis and Adjustment of High-Dimensional Data
in Respect to Sample Annotations
Collection of functions to connect the structure of the data with the information on the samples. Three types of associations are covered: 1. linear model of principal components. 2. hierarchical clustering analysis. 3. distribution of features-sample annotation associations. Additionally, the inter-relation between sample annotations can be analyzed. Simple methods are provided for the correction of batch effects and removal of principal components.
||impute, amap, gplots, MASS
||Martin Lauss <martin.lauss at med.lu.se>
||GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
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