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swamp (version 1.2.3)

Visualization, analysis and adjustment of high-dimensional data in respect to sample annotations.

Description

The package contains 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.

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Version

Install

install.packages('swamp')

Monthly Downloads

336

Version

1.2.3

License

GPL (>= 2)

Maintainer

Martin Lauss

Last Published

March 13th, 2013

Functions in swamp (1.2.3)

adjust.linearmodel

Batch adjustment using a linear model
quickadjust.zero

Batch adjustment by median-centering
dense.plot

Density plots of feature associations in observed and permuted data
hca.test

Tests for annotation differences among sample clusters
prince.plot

Heatmap of the associations between principal components and sample annotations
swamp-package

Visualization, analysis and adjustment of high-dimensional data in respect to sample annotations.
confounding

Heatmap of interrelation of sample annotations
prince.var.plot

ScreePlot of the data variation covered by the principal components
combat

ComBat algorithm to combine batches.
prince

Linear models of prinicipal conponents dependent on sample annotations
hca.plot

Dendrogram with according sample annotations
quickadjust.ref

Batch adjustment by median-scaling to a reference batch
feature.assoc

Associations of the features to a sample annotation in observed and reshuffled data.
kill.pc

Removes principal components from a data matrix
corrected.p

Correction of p-values for associations between features and sample annotation