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.
|Date of publication||2017-09-01 09:39:29 UTC|
|Maintainer||Martin Lauss <[email protected]>|
|License||GPL (>= 2)|
|Package repository||View on CRAN|
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