Package: AutoPipe 0.1.6

AutoPipe: Automated Transcriptome Classifier Pipeline: Comprehensive Transcriptome Analysis

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.

Authors:Karam Daka [cre, aut], Dieter Henrik Heiland [aut]

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8 exports 1.64 score 135 dependencies 6 mentions 302 downloads

Last updated 6 years agofrom:3220705495. Checks:OK: 7. Indexed: yes.

Exports:AutoPipe_tSNEcons_clustGroups_Supread_expression_fileSupervised_Cluster_Heatmaptop_supervisedTopPAMUnSuperClassifier

Dependencies:ALLannotateAnnotationDbiapeaplotaskpassbabelgeneBHBiobaseBiocGenericsBiocParallelBiostringsbitbit64blobcachemcliclusterclusterProfilercodetoolscolorspaceConsensusClusterPluscowplotcpp11crayoncurldata.tableDBIdigestDOSEdplyrenrichplotfansifarverfastmapfastmatchfgseaformatRfsfutile.loggerfutile.optionsgenericsGenomeInfoDbGenomeInfoDbDataggforceggfunggnewscaleggplot2ggplotifyggraphggrepelggtreeglueGO.dbGOSemSimgraphlayoutsgridExtragridGraphicsgsongtablehttrigraphIRangesisobandjsonliteKEGGRESTlabelinglambda.rlatticelazyevallifecyclemagrittrMASSMatrixmemoisemgcvmimemsigdbrmulttestmunsellnlmeopensslorg.Hs.eg.dbpamrpatchworkpillarpkgconfigplogrplyrpngpolyclippurrrqvalueR.methodsS3R.ooR.utilsR6RColorBrewerRcppRcppArmadilloRcppEigenreshape2rlangRSQLiteRtsneS4VectorsscalesscatterpiescrimeshadowtextsiggenessnowstringistringrsurvivalsyssystemfontstibbletidygraphtidyrtidyselecttidytreetreeiotweenrUCSC.utilsutf8vctrsviridisviridisLitewithrXMLxtableXVectoryulab.utilszlibbioc