An unsupervised fully-automated pipeline for transcriptome analysis or a supervised option to identify characteristic genes from predefined subclasses. We rely on the 'pamr' <http://www.bioconductor.org/packages//2.7/bioc/html/pamr.html> clustering algorithm to cluster the Data and then draw a heatmap of the clusters with the most significant genes and the least significant genes according to the 'pamr' algorithm. This way we get easy to grasp heatmaps that show us for each cluster which are the clusters most defining genes.
| Version: | 0.1.6 |
| Depends: | R (≥ 3.5.0) |
| Imports: | cluster , pamr , siggenes , annotate , fgsea , org.Hs.eg.db , RColorBrewer , ConsensusClusterPlus , Rtsne , clusterProfiler , msigdbr |
| Published: | 2019-02-27 |
| Author: | Karam Daka [cre, aut], Dieter Henrik Heiland [aut] |
| Maintainer: | Karam Daka <k.dacca at gmail.com> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | AutoPipe results |
| Reference manual: | AutoPipe.pdf |
| Package source: | AutoPipe_0.1.6.tar.gz |
| Windows binaries: | r-devel: AutoPipe_0.1.6.zip, r-release: AutoPipe_0.1.6.zip, r-oldrel: AutoPipe_0.1.6.zip |
| macOS binaries: | r-release: not available, r-oldrel: not available |
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