Comprehensive analysis of transciptome data

This package translates microarray expression data into metadata
  of reduced dimension. It provides various sample-centered and group-centered
  visualizations, sample similarity analyses and functional enrichment analyses.
  The underlying SOM algorithm combines feature clustering, multidimensional
  scaling and dimension reduction, along with strong visualization capabilities.
  It enables extraction and description of functional expression modules inherent
  in the data.

som, fastICA, tsne, scatterplot3d, pixmap, fdrtool, ape,
biomaRt, Biobase, arules

Henry Loeffler-Wirth <wirth@izbi.uni-leipzig.de> and Martin Kalcher <mkalcher@porkbox.net>

GeneExpression, DifferentialExpression, GeneSetEnrichment,
DataRepresentation, Visualization

Routines for simple graphs and network analysis. It can
    handle large graphs very well and provides functions for generating random
    and regular graphs, graph visualization, centrality methods and much more.

igraphdata, stats4, rgl, tcltk, graph, ape, scales

'adjacency.R' 'auto.R' 'assortativity.R' 'attributes.R'
'basic.R' 'bipartite.R' 'centrality.R' 'centralization.R'
'cliques.R' 'cocitation.R' 'cohesive.blocks.R' 'printr.R'
'community.R' 'components.R' 'console.R' 'conversion.R'
'data_frame.R' 'decomposition.R' 'degseq.R' 'demo.R'
'embedding.R' 'epi.R' 'fit.R' 'flow.R' 'foreign.R' 'games.R'
'glet.R' 'hrg.R' 'igraph-package.R' 'incidence.R' 'indexing.R'
'interface.R' 'iterators.R' 'layout.R' 'layout_drl.R'
'lazyeval.R' 'make.R' 'mgclust.R' 'minimum.spanning.tree.R'
'motifs.R' 'nexus.R' 'operators.R' 'other.R' 'package.R'
'palette.R' 'par.R' 'paths.R' 'plot.R' 'plot.common.R'
'plot.shapes.R' 'pp.R' 'print.R' 'random_walk.R' 'rewire.R'
'scan.R' 'scg.R' 'sgm.R' 'similarity.R' 'simple.R' 'sir.R'
'socnet.R' 'sparsedf.R' 'structural.properties.R'
'structure.info.R' 'test.R' 'tkplot.R' 'topology.R'
'triangles.R' 'utils.R' 'uuid.R' 'versions.R' 'weakref.R'
'zzz-deprecate.R'

A powerful and elegant high-level data visualization
  system inspired by Trellis graphics, with an emphasis on
  multivariate data. Lattice is sufficient for typical graphics needs,
  and is also flexible enough to handle most nonstandard requirements.
  See ?Lattice for an introduction.