Visualization, Analysis and Adjustment of High-Dimensional Data in Respect to Sample Annotations
Batch adjustment using a linear model
ComBat algorithm to combine batches.
Heatmap of interrelation of sample annotations
Correction of p-values for associations between features and sample an...
Density plots of feature associations in observed and permuted data
Associations of the features to a sample annotation in observed and re...
Dendrogram with according sample annotations
Tests for annotation differences among sample clusters
Removes principal components from a data matrix
Heatmap of the associations between principal components and sample an...
Linear models of prinicipal conponents dependent on sample annotations
ScreePlot of the data variation covered by the principal components
Batch adjustment by median-scaling to a reference batch
Batch adjustment by median-centering
tools:::Rd_package_title("swamp")
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.