Robust statistical inference for quantitative LC-MS proteomics

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Documentation for package ‘msqrob2’ version 1.17.0

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

.StatModel	The StatModel class for msqrob
data	Example data for 100 proteins
getCoef	Accessor functions for StatModel class
getCoef-method	Accessor functions for StatModel class
getContrast	Methods for StatModel class
getContrast-method	Methods for StatModel class
getDF	Accessor functions for StatModel class
getDF-method	Accessor functions for StatModel class
getDfPosterior	Accessor functions for StatModel class
getDfPosterior-method	Accessor functions for StatModel class
getFitMethod	Accessor functions for StatModel class
getFitMethod-method	Accessor functions for StatModel class
getModel	Accessor functions for StatModel class
getModel-method	Accessor functions for StatModel class
getSigma	Accessor functions for StatModel class
getSigma-method	Accessor functions for StatModel class
getSigmaPosterior	Accessor functions for StatModel class
getSigmaPosterior-method	Accessor functions for StatModel class
getVar	Accessor functions for StatModel class
getVar-method	Accessor functions for StatModel class
getVarPosterior	Accessor functions for StatModel class
getVarPosterior-method	Accessor functions for StatModel class
getVcovUnscaled	Accessor functions for StatModel class
getVcovUnscaled-method	Accessor functions for StatModel class
hypothesisTest	Parameter estimates, standard errors and statistical inference on differential expression analysis
hypothesisTest-method	Parameter estimates, standard errors and statistical inference on differential expression analysis
hypothesisTestHurdle	Parameter estimates, standard errors and statistical inference on differential expression analysis
hypothesisTestHurdle-method	Parameter estimates, standard errors and statistical inference on differential expression analysis
makeContrast	Make contrast matrix
msqrob	Methods to fit msqrob models with ridge regression and/or random effects using lme4
msqrob-method	Methods to fit msqrob models with ridge regression and/or random effects using lme4
msqrobAggregate	Method to fit msqrob models with robust regression and/or ridge regression and/or random effects It models multiple features simultaneously, e.g. multiple peptides from the same protein.
msqrobAggregate-method	Method to fit msqrob models with robust regression and/or ridge regression and/or random effects It models multiple features simultaneously, e.g. multiple peptides from the same protein.
msqrobGlm	Function to fit msqrob models to peptide counts using glm
msqrobHurdle	Function to fit msqrob hurdle models
msqrobHurdle-method	Function to fit msqrob hurdle models
msqrobLm	Function to fit msqrob models using lm and rlm
msqrobLmer	Function to fit msqrob models with ridge regression and/or random effects using lme4
msqrobQB	Function to fit msqrob models to peptide counts using glm
msqrobQB-method	Function to fit msqrob models to peptide counts using glm
pe	Example data for 100 proteins
show-method	The StatModel class for msqrob
smallestUniqueGroups	Smallest unique protein groups
StatModel	The StatModel class for msqrob
StatModel-class	The StatModel class for msqrob
StatModel-method	Methods for StatModel class
statModelAccessors	Accessor functions for StatModel class
statModelMethods	Methods for StatModel class
topFeatures	Toplist of DE proteins, peptides or features
varContrast	Methods for StatModel class
varContrast-method	Methods for StatModel class