plgem.pValue {plgem} | R Documentation

## Computation of PLGEM p-values

### Description

This function computes p-values for observed PLGEM signal-to-noise ratio (STN) values (typically obtained via a call to `plgem.obsStn`) from resampled STN values (typically obtained via a call to `plgem.resampledStn`).

### Usage

      plgem.pValue(observedStn, plgemResampledStn, verbose=FALSE)

### Arguments

`observedStn` | `list` containing a `matrix` of observed PLGEM-STN values; output of function `plgem.obsStn`.
`plgemResampledStn` | `list` containing a `matrix` of resampled PLGEM-STN values; output of function `plgem.resampledStn`.
`verbose` | `logical`; if `TRUE`, comments are printed out while running.

### Details

The p-value of each given observed STN value is computed based on the quantile that the given value occupies in the corresponding distribution of resampled PLGEM-STN values, based on the following relationship:

p-value = min(2*quantile, 2*(1-quantile))

### Value

A `matrix` with the same `dim`ensions and `dimnames` as the input `observedStn$PLGEM.STN`, where each entry represents the p-value of the corresponding observed PLGEM-STN value.

### Author(s)

Mattia Pelizzola mattia.pelizzola@gmail.com

Norman Pavelka normanpavelka@gmail.com

### 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`, `plgem.obsStn`, `plgem.resampledStn`, `plgem.deg`, `run.plgem`

### Examples

      data(LPSeset)
      LPSfit <- plgem.fit(data=LPSeset)
      LPSobsStn <- plgem.obsStn(data=LPSeset, plgemFit=LPSfit)
      head(LPSobsStn[["PLGEM.STN"]])
      set.seed(123)
      LPSresampledStn <- plgem.resampledStn(data=LPSeset, plgemFit=LPSfit)
      LPSpValues <- plgem.pValue(LPSobsStn, LPSresampledStn)
      head(LPSpValues)

[Package plgem version 1.59.2 Index]