Given an plmDE object containing preprocessed/normalized measures of the expression of a set of genes under different conditions as well as related values of quantitatively-measured covariates of interest, fitGAPLM tests each gene for differential expression under a model specified by the user. The test is conducted based on the significance of a full Model fit to the expression data when compared with the fit of a reduced model (F statistic). The variables of interest should be present in the full model and absent in the reduced. This method is very flexible and can fit count data (eg. expression measures from high-throughput sequencing) as well as microarray data. Using fitGAPLM, the user can choose to model the gene expression measures by any mixture of additive functions of the numerical variables with linear terms of the factorial information available. Each of these functions is approximated through a B-spline fit with the intercept of the spline constrained at zero for identifiability. Although fitGAPLM seems to take in a daunting amount of input, many of the inputs already set to sensible defaults, and models of the complexity represented in this class must be well thought out and each parameter requires careful consideration.
● Data Source:
CranContrib
● Keywords: models, regression
● Alias: fitGAPLM
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fitBspline
(Package: plmDE) :
Compute B-Spline Basis for Data
Provides a heuristic framework for fitting a set of B-spline basis functions to a set of data points under the constraint of a limited number of degrees of freedom.
● Data Source:
CranContrib
● Keywords: smooth
● Alias: fitBspline
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Given a model contained in a DEresults object, plot.DEresults plots the fit of the model on the expression data for a specified gene/probe.
● Data Source:
CranContrib
● Keywords: ~hplot
● Alias: plot.DEresults
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Creates an object which can hold expression data and other measurements of interest.
● Data Source:
CranContrib
● Keywords:
● Alias: plmDEmodel
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Given gene expression data as well as phenotypic measurements, plmDEmodel encodes them within a single object on which fitGAPLM and limmaPLM can be run.
● Data Source:
CranContrib
● Keywords:
● Alias: plmDEmodel.default
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This package is intended for the analysis of gene expression data which is accompanied by some quantitative measurements (such as weight or tumor size) for each sample. It provides a very flexible framework for testing numerous differential-expression-related hypotheses regarding such data. To properly formulate such hypotheses, one must have a solid grasp of the models on which they are founded, and I therefore provide an introduction to this methodology, which should facilitate successful use of the package.
● Data Source:
CranContrib
● Keywords: package
● Alias: plmDE, plmDE-package
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Returns the most significant genes in a DEresults object.
● Data Source:
CranContrib
● Keywords:
● Alias: mostDE
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Uses the methods of fitGAPLM to generate linear models of the class MArrayLM so that the moderated t and F methods of limma may be used to test for differential gene expression. See fitGAPLM for more a more in-depth description of the inputs.
● Data Source:
CranContrib
● Keywords:
● Alias: limmaPLM
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Prints out a short summary of the data contained with an Object.
● Data Source:
CranContrib
● Keywords: ~print
● Alias: info
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Returns a short overview of the data contained plmDE objects.
● Data Source:
CranContrib
● Keywords: ~print
● Alias: info.plmDE
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providing 
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