icaSetStransky


  Object of class <code><a rd-options="" href="/link/IcaSet?package=MineICA&version=1.12.0" data-mini-rdoc="MineICA::IcaSet">IcaSet</a></code> containing an ICA
  decomposition calculated by the FastICA algorithm
  (through matlab function "icasso") on bladder cancer
  expression data measured on HG-U133-95a and HG-U133-95av2
  Affymetrix microarrays. It contains 20 independent
  components. The original expression data contain 63 tumor
  samples and were normalized by RMA with
  log2-transformation.


datasets

The goal of MineICA is to perform Independent Component
Analysis (ICA) on multiple transcriptome datasets, integrating
additional data (e.g molecular, clinical and pathological).
This Integrative ICA helps the biological interpretation of the
components by studying their association with variables (e.g
sample annotations) and gene sets, and enables the comparison
of components from different datasets using correlation-based
graph.

Anne Biton

MineICA

Analysis of an ICA decomposition obtained on genomics data

icaSetStransky function

Object of class <code><a href="IcaSet" rd-options="">IcaSet</a></code> containing an ICA
  decomposition calculated by the FastICA algorithm
  (through matlab function "icasso") on bladder cancer
  expression data measured on HG-U133-95a and HG-U133-95av2
  Affymetrix microarrays. It contains 20 independent
  components. The original expression data contain 63 tumor
  samples and were normalized by RMA with
  log2-transformation.

icaSetStransky: IcaSet-object containing a FastICA decomposition of gene expression microarrray-based data of bladder cancer samples.

Description

Arguments

References