Clust.exampleE


  This data is an artificial example of the mean gene expression levels.


datasets

Most analyses of Affymetrix GeneChip data (including tranditional 3' arrays and exon arrays and Human Transcriptome Array 2.0) are based on point estimates of expression levels and ignore the uncertainty of such estimates. By propagating uncertainty to downstream analyses we can improve results from microarray analyses. For the first time, the puma package makes a suite of uncertainty propagation methods available to a general audience. In additon to calculte gene expression from Affymetrix 3' arrays, puma also provides methods to process exon arrays and produces gene and isoform expression for alternative splicing study. puma also offers improvements in terms of scope and speed of execution over previously available uncertainty propagation methods. Included are summarisation, differential expression detection, clustering and PCA methods, together with useful plotting functions.

Xuejun Liu

puma

Propagating Uncertainty in Microarray Analysis(including
Affymetrix tranditional 3' arrays and exon arrays and Human
Transcriptome Array 2.0)

Clust.exampleE function

A 700x20 matrix including 700 genes and 20 chips. Every 100 genes belong to one cluster from the first gene. 
  There are 7 clusters.

Format

Liu, X. Lin, K., Andersen, B. Rattray, M. (2007) Including probe-level uncertainty in model-based gene expression clustering, BMC Bioinformatics, 8(98).

Source

This data is an artificial example of the mean gene expression levels.

Clust.exampleE: The example data of the mean gene expression levels

Description

Usage

Arguments

Format

Source

See Also