Weighted.matrixModel: Weighted.matrixModel

In Babulab-bioc/MSiP: 'MassSpectrometry' Interaction Prediction

Description

This function computes the weighted matrix model for instances (e.g., bait-prey interactions (BPIs)) in the data.frame.The output of the weighted matrix model includes the number of experiments for which the pair of proteins is co-purified (i.e., k) and -1*log(P-value) of the hypergeometric test (i.e., logHG) given the experimental overlap value, each protein's total number of observed experiments, and the total number of experiments (Drew et al., 2017).

Usage

Weighted.matrixModel(datInput)

Arguments

datInput

Data frame with column names: Experiment.id, Replicate, Bait, Prey, and count (i.e., prey count).

Value

Data frame containing bait-prey pairs with k (i.e.,number of co-purifications) & logHG (i.e., $-1$*log(P-val) of the hypergeometric test)

Author(s)

Matineh Rahmatbakhsh, [e-mail]

References

Drew, K., Lee, C., Huizar, R. L., Tu, F., Borgeson, B., McWhite, C. D., et al. (2017). Integration of over 9,000 mass spectrometry experiments builds a global map of human protein complexes. Mol. Syst. Biol. 13, 932.

Examples

data(SampleDatInput)
datScoring <- Weighted.matrixModel(SampleDatInput)
head(datScoring)

Babulab-bioc/MSiP documentation built on Dec. 17, 2021, 9:52 a.m.