# nullDistDoublyTestedEdges: Null distribution of number of reciprocated, unreciprocated... In ppiStats: Protein-Protein Interaction Statistical Package

## Description

Calculate the null distribution of the number of reciprocated, unreciprocated and missing edges in a stochastic model where each edge is tested twice.

## Usage

 `1` ```nullDistDoublyTestedEdges(deltaMax, n, pFP, pFN) ```

## Arguments

 `deltaMax` Integer. Distributions will be calculated for model parameter delta`=0, 1, 2, ..., deltaMax`. `n` Integer. The parameter n of the model. `pFP` Numeric. The parameter pFP of the model. `pFN` Numeric. The parameter pFN of the model.

## Details

The model is described in the vignette Stochastic and systematic errors in PPI data, by looking at unreciprocated in- or out-edges by W. Huber, T. Chiang and R. Gentleman.

This function can be quite slow, its runtime grows quickly with `deltaMax` (and is roughly independent of `n`, `pFP`, `pFN`). The example below should take only a few seconds on a reasonable computer, though.

## Value

3d array with dimensions `nMax+1` x `nMax+1` x `deltaMax+1` whose element `p[nr+1, nu+1, delta+1]` is the corresponding joint probability. `nMax+1` is calculated (probably too conservatively) by the function to make sure that no probability leaks out of the array.

## Author(s)

Wolfgang Huber http://www.ebi.ac.uk/huber

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10``` ```p = nullDistDoublyTestedEdges(32, 1000, pFP=0.001, pFN=0.15) if(interactive() && require("RColorBrewer")) for(k in 1:dim(p)[3]) { image(sqrt(p[,,k]), xlab=expression(N[rec]), ylab=expression(N[unrec]), main = expression(P(N[rec], N[unrec]~";"~ delta^"*", n, p[FP], p[FN])), x = 1:dim(p)[1], y = 1:dim(p)[2], col = colorRampPalette(brewer.pal(9, "GnBu"))(256)) text(35, 35, paste("delta", k, sep="=")) } ```

ppiStats documentation built on Nov. 1, 2018, 3:50 a.m.