TTCA: Transcript Time Course Analysis

The analysis of microarray time series promises a deeper insight into the dynamics of the cellular response following stimulation. A common observation in this type of data is that some genes respond with quick, transient dynamics, while other genes change their expression slowly over time. The existing methods for the detection of significant expression dynamics often fail when the expression dynamics show a large heterogeneity, and often cannot cope with irregular and sparse measurements. The method proposed here is specifically designed for the analysis of perturbation responses. It combines different scores to capture fast and transient dynamics as well as slow expression changes, and deals with low replicate numbers and irregular sampling times. The results are given in the form of tables linked to figures. These allow to quickly recognize the relevance of detection, to identify possible false positives and to distinguish between changes in the early and later expression. An extension of the method allows the analysis of the expression dynamics of functional groups of genes, providing a quick overview of the cellular response. The performance of this package was tested on microarray data derived from lung cancer cells stimulated with epidermal growth factor. See publication "TTCA: An R package for the identification of differentially expressed genes in time course microarray data".

Version: 0.1.0
Depends: R (≥ 2.10)
Imports: Matrix, quantreg, tcltk2, RISmed, VennDiagram, MASS
Published: 2016-06-20
Author: Marco Albrecht
Maintainer: Marco Albrecht <marco.albrecht at>
License: EUPL
NeedsCompilation: no
CRAN checks: TTCA results


Reference manual: TTCA.pdf
Package source: TTCA_0.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X Mavericks binaries: r-release: TTCA_0.1.0.tgz, r-oldrel: TTCA_0.1.0.tgz


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