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MSiP
View on CRAN: Click
here
Download and install MSiP package within the R console
Install from CRAN:
install.packages("MSiP")
Install from Github:
library("remotes")
install_github("cran/MSiP")
Install by package version:
library("remotes")
install_version("MSiP", "1.3.7")
Attach the package and use:
library("MSiP")
Maintained by
Matineh Rahmatbakhsh
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-06-17
Latest Update: 2021-06-17
Description:
The 'MSiP' is a computational approach to predict protein-protein interactions from large-scale affinity purification mass 'spectrometry' (AP-MS) data. This approach includes both spoke and matrix models for interpreting AP-MS data in a network context. The "spoke" model considers only bait-prey interactions, whereas the "matrix" model assumes that each of the identified proteins (baits and prey) in a given AP-MS experiment interacts with each of the others. The spoke model has a high false-negative rate, whereas the matrix model has a high false-positive rate. Although, both statistical models have merits, a combination of both models has shown to increase the performance of machine learning classifiers in terms of their capabilities in discrimination between true and false positive interactions.
How to cite:
Matineh Rahmatbakhsh (2021). MSiP: 'MassSpectrometry' Interaction Prediction. R package version 1.3.7, https://cran.r-project.org/web/packages/MSiP
Previous versions and publish date:
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Other R packages that MSiP depends,
imports, suggests or enhances
Functions, R codes and Examples using
the MSiP R package
Some associated functions: SampleDatInput . Weighted.matrixModel . cPASS . diceCoefficient . jaccardCoefficient . overlapScore . rfTrain . simpsonCoefficient . svmTrain . testdfClassifier .
Some associated R codes: SampleDatInput.R . Weighted.matrixModel.R . cPASS.R . diceCoefficient.R . jaccardCoefficient.R . overlapScore.R . rfTrain.R . simpsonCoefficient.R . svmTrain.R . testdfClassifier.R . Full MSiP package functions and examples
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