mergeComplexes {apComplex} | R Documentation |
Repeatedly applies the function LCdelta
to make combinations of columns in the affiliation matrix representing the protein complex membership graph (PCMG) for AP-MS data.
mergeComplexes(PCMG, adjMat, simMat = NULL, sensitivity = 0.75, specificity = 0.995, Beta = 0)
PCMG |
Current PCMG estimate |
adjMat |
Adjacency matrix of bait-hit data from an AP-MS experiment. Rows correspond to baits and columns to hits. |
simMat |
An optional square matrix with entries between 0 and 1. Rows and columns correspond to the proteins in the experiment, and should be reported in the same order as the columns of adjMat . Higher values in this matrix are interpreted to mean higher similarity for protein pairs. |
sensitivity |
Believed sensitivity of AP-MS technology. |
specificity |
Believed specificity of AP-MS technology. |
Beta |
Optional additional parameter for the weight to give data in simMat in the logistic regression model. |
The local modeling algorithm for AP-MS data described by Scholtens and
Gentleman (2004) and Scholtens, Vidal, and Gentleman (submitted) uses a
two-component measure of protein complex estimate quality, namely P=LxC.
Columns in cMat
represent individual complex estimates. The algorithm
works by starting with a maximal BH-complete subgraph estimate of cMat
,
and then improves the estimate by combining columns such that P=LxC increases.
When proposing combinations of columns comp1
and comp2
in
cMat
, the proposal is accepted if the output from LCdelta
(the
log of LxC) is greater than zero. mergeComplexes
performs all column
combinations until no more combinations result in an output from
LCdelta
greater than zero.
An affiliation matrix representing the estimated PCMG. The number of rows and
the row labels of the matrix will be the same as adjMat
. The number of columns will be less than or equal to the number of columns in adjMat
.
Denise Scholtens
Scholtens D and Gentleman R. Making sense of high-throughput protein-protein interaction data. Statistical Applications in Genetics and Molecular Biology 3, Article 39 (2004).
Scholtens D, Vidal M, and Gentleman R. Local modeling of global interactome networks. Submitted.
LCdelta
,bhmaxSubgraph
,findComplexes
data(apEX) PCMG0 <- bhmaxSubgraph(apEX) PCMG1 <- mergeComplexes(PCMG0,apEX,sensitivity=.7,specificity=.75)