.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 |