estimateCCMErrorRates: Estimate false positive and false negative error...
In Bioconductor/ppiStats: Protein-Protein Interaction Statistical Package

Description Usage Arguments Details Value Author(s) References Examples

Estimate false positive and false negative error probabilities for complex comembership edges using a protein complex interactome gold standard

1 2	estimateCCMErrorRates(m,GS,filterSystematic=TRUE, obsPropThresh=1,SystematicpThresh=.01)

`m`	The bait to prey data adjacency matrix. Baits index the rows and prey index the columns.
`GS`	A gold standard protein complex interaction incidence matrix. Proteins index the rows and protein complexes index the columns.
`filterSystematic`	A logical. If TRUE, all baits with with highly uneven directed degree will be filtered out of the data.
`obsPropThresh`	A numeric between 0 and 1. The proportion of tested proteins found within a protein complex needed to keep that protein complex within the gold standard set.
`SystematicpThresh`	A numeric between 0 and 1. The p-value threshold by which systematic errors are filtered.

The model is described in the manuscript Estimating node degree in bait-prey graphs. by D. Scholtens et al.

A list:

`globalpTP`	A numeric between 0 and 1. Estimate of pTP.
`globalpTPSE`	A numeric. Estimate of standard error of globalpTP estimate.
`globalpFP`	A numeric between 0 and 1. Estimate of pFP.
`pTP95CI`	A vector of length 2. 95 percent confidence interval upper and lower bounds for globalpTP estimate.
`pFP95CI`	A vector of length 2. 95 percent confidence interval upper and lower bounds for globalpFP estimate.
`nEligComplexes`	A numeric. Number of complexes from GS that met obsPropThresh criteria.
`nEligBaits`	A numeric. Total number of eligible baits in GS set.
`nEligEdges`	A numeric. Total number of eligible edges in GS set.
`nBaitsInComplexes`	A vector. Number of baits in each eligible complex.
`complexSizes`	A vector. Size of each complex in GS set.

T. Chiang and D. Scholtens

Scholtens D, Chiang T, Huber W, Gentleman R. Estimating node degree in bait-prey graphs. Bioinformatics. To appear.

data(Ho2002BPGraph, package = "ppiData")
data(ScISIC, package = "ScISI")
Ho2002mat <- as(Ho2002BPGraph,"matrix")
estimateCCMErrorRates(Ho2002mat,ScISIC)$globalpTP