pandaR (version 1.4.2)

panda: Passing Messages between Biological Networks to Refine Predicted Interactions

Description

This function runs the PANDA algorithm

Usage

panda(motif, expr = NULL, ppi = NULL, alpha = 0.1, hamming = 0.001,
  iter = NA, output = c("regulatory", "coexpression", "cooperative"),
  zScale = TRUE, progress = FALSE, randomize = c("None", "within.gene",
  "by.gene"), cor.method = "pearson", scale.by.present = FALSE,
  edgelist = FALSE, remove.missing.ppi = FALSE,
  remove.missing.motif = FALSE, remove.missing.genes = FALSE)

Arguments

motif

A motif dataset, a data.frame, matrix or exprSet containing 3 columns. Each row describes an motif associated with a transcription factor (column 1) a gene (column 2) and a score (column 3) for the motif.

expr

An expression dataset, as a genes (rows) by samples (columns) data.frame

ppi

A Protein-Protein interaction dataset, a data.frame containing 3 columns. Each row describes a protein-protein interaction between transcription factor 1(column 1), transcription factor 2 (column 2) and a score (column 3) for the interaction.

alpha

value to be used for update variable, alpha (default=0.1)

hamming

value at which to terminate the process based on hamming distance (default 10^-3)

iter

sets the maximum number of iterations PANDA can run before exiting.

output

a vector containing which networks to return. Options include "regulatory", "coregulatory", "cooperative".

zScale

Boolean to indicate use of z-scores in output. False will use [0,1] scale.

progress

Boolean to indicate printing of output for algorithm progress.

randomize

method by which to randomize gene expression matrix. Default "None". Must be one of "None", "within.gene", "by.genes". "within.gene" randomization scrambles each row of the gene expression matrix, "by.gene" scrambles gene labels.

cor.method

Correlation method, default is "pearson".

scale.by.present

Boolean to indicate scaling of correlations by percentage of positive samples.

edgelist

Boolean to indicate if edge lists instead of matrices should be returned.

remove.missing.ppi

Boolean to indicate whether TFs in the PPI but not in the motif data should be removed.

remove.missing.motif

Boolean to indicate whether genes targeted in the motif data but not the expression data should be removed.

remove.missing.genes

Boolean to indicate whether genes in the expression data but lacking information from the motif prior should be removed.

Value

• An object of class "panda" containing matrices describing networks achieved by convergence with PANDA algorithm. "regNet" is the regulatory network "coregNet" is the coregulatory network "coopNet" is the cooperative network

References

Glass K, Huttenhower C, Quackenbush J, Yuan GC. Passing Messages Between Biological Networks to Refine Predicted Interactions. PLoS One. 2013 May 318(5):e64832.

Examples

data(pandaToyData)
pandaRes <- panda(pandaToyData$motif,
           pandaToyData$expression,pandaToyData$ppi,hamming=.1,progress=TRUE)