dyebias.monotonicity {dyebias}R Documentation

Calculate the degree of monotonicity of the dye bias across the slides.

Description

If you order genes by their iGSDB, and hybridizations by slide bias, the graphs of each gene should form a 'fan' out of the origin (see also dyebias.trendplot). This function gives measure of the extent to which this is true.

Usage

  dyebias.monotonicity(data,
                       iGSDBs, dyebias.percentile = 5,
                       order = NULL)

Arguments

data The marrayNorm to determine the degree of monotonicity for
iGSDBs A data frame with intrinsic gene-specific dye biases, the same as that used in dyebias.apply.correction, probably returned by
dyebias.estimate.iGSDBs; see there for documentation.
dyebias.percentile The percentile of intrinsic gene specific dye biases (iGSDBs) for which to highlight the reporters. Default should suffice in almost all cases.
order If order==NULL, the slides are sorted by increasing slide bias prior to boxplotting. This is typically done for data that is not yet dye bias corrected. (This order is also returned in the object returned). If order!=NULL, the slides are put into this order first. This is typically done for a dye bias-corrected data set, using the order of the uncorrected set.

Details

The total dye bias appears to be the product of iGSDB and slide bias. In other words, it is monotonous (always increasing or always decreasing), both with respect to the intrinsic gene specific dye bias and with respect to the slide bias. This function orders genes by their iGSDB and the slides by slide bias. Subsequently a linear regression of each gene is done, with x being the slide bias rank, (not the slide bias itself), and y being the M. The slopes of each linear regression line should be an increasing array of values, representing the 'fan' of lines. The degree to which this array is increasing is tested using the Mann-Kendall test, and is returned. In the case of uncorrected data, tau is generally larger than 0.3. After correction, tau should be close to zero.

Value

A dyebias.monotonicity uses cor.test, which returns htest object. To this list an extra element, order, is added, which indicates the ordering of the data set by slide bias. The degree of monotonicity is indicated by the estimate element; its signficance by the p.value element.

Note

This function can take very long to compute, since it calculates regressions for each gene.

Author(s)

Philip Lijnzaad p.lijnzaad@umcutrecht.nl

References

Margaritis, T., Lijnzaad, P., van~Leenen, D., Bouwmeester, D., Kemmeren, P., van~Hooff, S.R and Holstege, F.C.P. (2009). Adaptable gene-specific dye bias correction for two-channel DNA microarrays. Molecular Systems Biology, submitted

See Also

dyebias.trendplot, dyebias.monotonicityplot

Examples

                                       

  cat("monotonicity before correction")
  monotonicity <- dyebias.monotonicity(data=data.norm,
                                       iGSDBs=iGSDBs.estimated, 
                                       order=NULL)
  monotonicity

  cat("monotonicity after correction")

  dyebias.monotonicity(data=correction$data.corrected,
                                       iGSDBs=iGSDBs.estimated, 
                                       order= monotonicity$order)


[Package dyebias version 1.2.1 Index]