setGpar: Set graphical parameters for PLGEM fitting evaluation plots

In plgem: Detect differential expression in microarray and proteomics datasets with the Power Law Global Error Model (PLGEM)

Description

Function to set graphical parameters for PLGEM fitting evaluation plots produced by function plgem.fit.

Usage

  setGpar(minLnM=NULL, maxLnM=NULL, minLnSD=NULL, maxLnSD=NULL,
    minRes=NULL, maxRes=NULL)

Arguments

minLnM	minimum 'ln(mean)' value in upper left plot.
maxLnM	maximum 'ln(mean)' value in upper left plot.
minLnSD	minimum 'ln(sd)' value in upper left plot.
maxLnSD	maximum 'ln(sd)' value in upper left plot.
minRes	minimum 'residual' value in upper right plot.
maxRes	maximum 'residual' value in upper right plot.

Details

A call to setGpar() is the recommended way to set graphical parameters in plgem.fit. If parameters are left unspecified, suitable defaults will be found by plgem.fit.

Value

A list of six elements:

minLnM	minimum 'ln(mean)' value in upper left plot.
maxLnM	maximum 'ln(mean)' value in upper left plot.
minLnSD	minimum 'ln(sd)' value in upper left plot.
maxLnSD	maximum 'ln(sd)' value in upper left plot.
minRes	minimum 'residual' value in upper right plot.
maxRes	maximum 'residual' value in upper right plot.

Author(s)

Norman Pavelka [e-mail]

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. 2008 Apr; 7(4):631-44; http://www.mcponline.org/cgi/content/abstract/7/4/631.

See Also

plgem.fit, run.plgem

Examples

  setGpar(minLnM=-1, maxLnM=8)

plgem documentation built on Nov. 8, 2020, 5:31 p.m.