run.plgem {plgem}R Documentation

Wrapper for Power Law Global Error Model (PLGEM) analysis method

Description

This function automatically performs PLGEM fitting and evaluation, determination of observed and resampled PLGEM STN values, and selection of differentially expressed genes/proteins (DEG) using the PLGEM method.

Usage

  run.plgem(esdata, signLev=0.001, rank=100, covariateNumb=1,
    baselineCondition=1, Iterations="automatic", fitting.eval=TRUE,
    plotFile=FALSE, writeFiles=FALSE, Verbose=FALSE)

Arguments

esdata an object of class ExpressionSet; see Details for important information on how the phenoData slot of this object will be interpreted by the function.
signLev numeric vector; significance level(s) for the DEG selection. Value(s) must be in (0,1).
rank integer (or coercible to integer); the number of genes or proteins to be selected according to their PLGEM-STN rank. Only used if number of available replicates is too small to perform resampling (see Details).
covariateNumb integer (or coercible to integer); the covariate used to determine on which samples to fit plgem.
baselineCondition integer (or coercible to integer); the condition to be treated as the baseline.
Iterations number of iterations for the resampling step; if "automatic" it is automatically determined.
fitting.eval logical; if TRUE, the fitting is evaluated generating a diagnostic plot.
plotFile logical; if TRUE, the generated plot is written on a file.
writeFiles logical; if TRUE, the generated list of DEG is written on disk file(s).
Verbose logical; if TRUE, comments are printed out while running.

Details

The ‘covariateNumb’ covariate (the first one by default) of the phenoData of the ExpressionSet ‘data’ is expected to contain the necessary information about the experimental design. The values of this covariate must be sample labels, that have to be identical for samples to be treated as replicates. In particular, the ExpressionSet ‘esdata’ must have at least two conditions in the ‘covariateNumb’ covariate; by default the first one is considered the baseline.

The model is fitted on the most replicated condition. When more conditions exist with the max number of replicates, the condition providing the best fit is chosen.

If less than 3 replicates are provided for the condition used for fitting, then the selection is based on ranking according to the observed PLGEM STN values. In this case the first ‘rank’ genes or proteins are selected for each comparison.

Otherwise DEG are selected comparing the observed and resampled PLGEM STN values at the ‘signLev’ significance level(s), based on p-values obtained via a call to function plgem.pValue. See References for details.

Value

This function returns a list with a number of items that is equal to the number of different significance levels (‘signLev’) used as input. Each item is again a list, whose number of items correspond to the number of performed comparisons, i.e. the number of conditions defined in the phenoData of ‘esdata’ minus the baseline. In each list-item the values are the observed PLGEM STN values of the significantly changing genes or proteins, named according to the rownames of the exprs of ‘esdata’.

Author(s)

Mattia Pelizzola mattia.pelizzola@gmail.com

Norman Pavelka nxp@stowers-institute.org

References

Pavelka N, Pelizzola M, Vizzardelli C, Capozzoli M, Splendiani A, Granucci F, Ricciardi-Castagnoli P. A power law global error model for the identification of differentially expressed genes in microarray data. BMC Bioinformatics. 2004 Dec 17;5:203.; http://www.biomedcentral.com/1471-2105/5/203

Pavelka N, Fournier ML, Swanson SK, Pelizzola M, Ricciardi-Castagnoli P, Florens L, Washburn MP. Statistical similarities between transcriptomics and quantitative shotgun proteomics data. Mol Cell Proteomics. 2007 Nov 19; http://www.mcponline.org/cgi/content/abstract/M700240-MCP200v1

See Also

plgem.fit, plgem.obsStn, plgem.resampledStn, plgem.pValue, plgem.write.summary

Examples

  data(LPSeset)
  set.seed(123)
  LPSdegList <- run.plgem(esdata=LPSeset)

[Package plgem version 1.14.0 Index]