R: Visualization, Analysis and Adjustment of High-Dimensional Data in Respect to Sample Annotations

# Visualization, Analysis and Adjustment of High-Dimensional Data in Respect to Sample Annotations

## Documentation for package ‘swamp’ version 1.5.1

- DESCRIPTION file

## Help Pages

swamp-package | Visualization, Analysis and Adjustment of High-Dimensional Data in Respect to Sample Annotations
adjust.linearmodel | Batch adjustment using a linear model
combat | ComBat algorithm to combine batches.
confounding | Heatmap of interrelation of sample annotations
corrected.p | Correction of p-values for associations between features and sample annotation
dense.plot | Density plots of feature associations in observed and permuted data
feature.assoc | Associations of the features to a sample annotation in observed and reshuffled data.
hca.plot | Dendrogram with according sample annotations
hca.test | Tests for annotation differences among sample clusters
kill.pc | Removes principal components from a data matrix
prince | Linear models of prinicipal conponents dependent on sample annotations
prince.plot | Heatmap of the associations between principal components and sample annotations
prince.var.plot | ScreePlot of the data variation covered by the principal components
quickadjust.ref | Batch adjustment by median-scaling to a reference batch
quickadjust.zero | Batch adjustment by median-centering
swamp | Visualization, Analysis and Adjustment of High-Dimensional Data in Respect to Sample Annotations