rHVDM (version 1.38.0)

estimerrors: computes the standard deviation of the measurement error using pre-calculated tables specific to the plattform or user-defined table

Description

This method takes as main input and ExpressionSet object, and using pre-calculated tables contained in rHVDM, it returns the same object with an extra slot that contains the standard deviation of the measurement error which is indispensable to then run rHVDM proper. The table can be user-defined. To check which tables are stored in rHVDM, just run the command without arguments (estimerrors()), it will return a list of the supported rHVDM plattforms. All parameters of this function are optional, see below for details on the effect of omitting one or more of them. The method assumes the the amount of error is dependent both on the particular microarray and the signal intensity. For more details on how it is computed, please refer to the textual description of rHVDM.

Usage

estimerrors(eset,plattid,refchips,errtable)

Arguments

eset

an object of class ExpressionSet (Biobase), every time this parameter is omitted the function returns a list of supported plattforms (identifier+plattform description).

plattid

an optional argument (character format) allowing to specify the plattform identifiers. These identifiers are rHVDM specific. Any identifier will be overriden by a table given as input of the errtable argument. In future versions of rHVDM, if this argument and the errtable are missing, a search will be done among the supported plattforms to find a matching plattform, based on the individual genes identifiers. For now, omission of both arguments will be conductive to outputting a list of supported plattforms.

refchips

a vector of names or column indexes compatible with the ExpressionSet useds (note that this compatibility is not verified by the function, it is up to the user to supply compatible array names). Some microarray might be known to be of not very good quality and although the measurement error will be computed for these chips it is better to leave them out of early stages of the computation. The list to be input should typically contain the least noisy microarrays. This parameter is optional and if omitted, all microarrays are used.

errtable

a nx2 table in matrix format. The first column of the matrix should contain reference log of signals in ascending order and the second the variance corresponding to the signals.

Value

Normally an updated eset is returned. In case some crucial element is missing, the original eset is returned. If the latter is missing too a list of supported plattform is returned (thus, when using this function, it is better to be careful of what lies at the LHS of the assignement arrow).

Details

Local interpolation and individual array normalisation are used to estimate the standard deviation of the measurement error for each individual transcript on each microarray. The precise method is laid out in the paper cited below, with some minor modifications.

References

M. Barenco, D. Tomescu, D. Brewer, R. Callard, J. Stark, M. Hubank (2006) Ranked predictions of p53 targets using Hidden Variable Dynamic Modelling. Genome Biology, V7(3), R25.

See Also

HVDMcheck,training,screening,fitgene

Examples

data(HVDMexample)
fiveGybis<-estimerrors(eset=fiveGyMAS5,plattid="affy_HGU133A",refchips=leastnoisychips)
#leastnoisy chips is a list of three chips identifiers stored in the HVDMexample data bundle