swamp: Visualization, analysis and adjustment of high-dimensional data in respect to sample annotations.
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.
- Martin Lauss
- Date of publication
- 2013-03-13 14:11:11
- Martin Lauss <firstname.lastname@example.org>
- GPL (>= 2)
- 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...
- Density plots of feature associations in observed and...
- Associations of the features to a sample annotation in...
- Dendrogram with according sample annotations
- Tests for annotation differences among sample clusters
- Removes principal components from a data matrix
- Linear models of prinicipal conponents dependent on sample...
- Heatmap of the associations between principal components and...
- ScreePlot of the data variation covered by the principal...
- Batch adjustment by median-scaling to a reference batch
- Batch adjustment by median-centering
- Visualization, analysis and adjustment of high-dimensional...
Files in this package