monotoneDirection {ORCME}

The monotone means under increasing/decreasing trend

Description

The function calculates the likelihood for the increasing and decreasing trend in the dose response for all the given genes separately gene-by-gene. The trend with the higher likelihood is chosen and the isotonic regression is applied on the means.

Usage

monotoneDirection(geneData, doseData)

Arguments

geneData

gene expression matrix for all genes

doseData

indicates the dose levels

Value

A list with components

direction

the direction with the higher likelihood of increasing (indicated by "up") or decreasing (indicated by "dn") trend.

incData

isotonic means with respect to dose for those genes that were classified as following the increasing trend.

decData

isotonic means with respect to dose for those genes that were classified as following the decreasing trend.

obsincData

observed gene expression matrix for those genes that were classified as following the increasing trend.

obsdecData

observed gene expression matrix for those genes that were classified as following the decreasing trend.

arrayMean

isotonic means with respect to dose for all genes.

Author(s)

Adetayo Kasim, Martin Otava and Tobias Verbeke

References

Lin D., Shkedy Z., Yekutieli D., Amaratunga D., and Bijnens, L. (editors). (2012) Modeling Dose-response Microarray Data in Early Drug Development Experiments Using R. Springer.

Cheng, Y. and Church, G. M. (2000). Biclustering of expression data. In: Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology, 1, 93-103.

See Also

ORCME, plotIsomeans

Examples

  data(doseData)
  data(geneData)

  dirData <- monotoneDirection(geneData = geneData,doseData = doseData)

  ## direction of monotone trend
  Direction <- dirData$direction
  ## Isotonic means for upward genes
  incData <- as.data.frame(dirData$incData)
  ##Isotonic means for downward genes
  decData <- as.data.frame(dirData$decData)
  ## observd data upward genes
  obsIncData <- as.data.frame(dirData$obsincData)
  ## observed data for downward genes
  obsDecData <- as.data.frame(dirData$obsdecData)
  ## isotonic means for all genes
  isoMeans <- as.data.frame(dirData$arrayMean)