PomaRankProd: Rank Product/Rank Sum Analysis for Mass Spectrometry Data

In POMA: User-friendly Workflow for Pre-processing and Statistical Analysis of Mass Spectrometry Data

Description

PomaRankProd() performs the Rank Product method to identify differential feature concentration/intensity.

Usage

PomaRankProd(
  data,
  logged = TRUE,
  logbase = 2,
  paired = NA,
  cutoff = 0.05,
  method = "pfp"
)

Arguments

data	A MSnSet object. First pData column must be the subject group/type.
logged	If "TRUE" (default) data have been previously log transformed.
logbase	Numerical. Base for log transformation.
paired	Number of random pairs generated in the function, if set to NA (default), the odd integer closer to the square of the number of replicates is used.
cutoff	The pfp/pvalue threshold value used to select features.
method	If cutoff is provided, the method needs to be selected to identify features. "pfp" uses percentage of false prediction, which is a default setting. "pval" uses p-values which is less stringent than pfp.

Value

A list with all results for Rank Product analysis including tables and plots.

Author(s)

Pol Castellano-Escuder

References

Breitling, R., Armengaud, P., Amtmann, A., and Herzyk, P.(2004) Rank Products: A simple, yet powerful, new method to detect differentially regulated genes in replicated microarray experiments, FEBS Letter, 57383-92

Hong, F., Breitling, R., McEntee, W.C., Wittner, B.S., Nemhauser, J.L., Chory, J. (2006). RankProd: a bioconductor package for detecting differentially expressed genes in meta-analysis Bioinformatics. 22(22):2825-2827

Del Carratore, F., Jankevics, A., Eisinga, R., Heskes, T., Hong, F. & Breitling, R. (2017). RankProd 2.0: a refactored Bioconductor package for detecting differentially expressed features in molecular profiling datasets. Bioinformatics. 33(17):2774-2775

POMA documentation built on Nov. 8, 2020, 6:26 p.m.