swamp (1.4.1)

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.

Maintainer: Martin Lauss
Author(s): Martin Lauss

License: GPL (>= 2)

Uses: amap, gplots, impute, MASS

Released over 1 year ago.