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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.
| Version: | 1.5.1 |
| Depends: | impute, amap, gplots, MASS |
| Imports: | methods |
| Published: | 2019-12-06 |
| Author: | Martin Lauss |
| Maintainer: | Martin Lauss <martin.lauss at med.lu.se> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| CRAN checks: | swamp results |
| Reference manual: | swamp.pdf |
| Package source: | swamp_1.5.1.tar.gz |
| Windows binaries: | r-devel: swamp_1.5.1.zip, r-release: swamp_1.5.1.zip, r-oldrel: swamp_1.5.1.zip |
| macOS binaries: | r-release (arm64): swamp_1.5.1.tgz, r-oldrel (arm64): swamp_1.5.1.tgz, r-release (x86_64): swamp_1.5.1.tgz, r-oldrel (x86_64): swamp_1.5.1.tgz |
| Old sources: | swamp archive |
| Reverse imports: | DExMA |
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