DESeq2-package
(Package: DESeq2) :
DESeq2 package for differential analysis of count data
The main functions for differential analysis are DESeq and results. See the examples at DESeq for basic analysis steps. Two transformations offered for count data are the "regularized logarithm", rlog, and varianceStabilizingTransformation. For more detailed information on usage, see the package vignette, by typing vignette("DESeq2"), or the workflow linked to on the first page of the vignette. All support questions should be posted to the Bioconductor support site: http://support.bioconductor.org.
DESeqDataSet is a subclass of RangedSummarizedExperiment, used to store the input values, intermediate calculations and results of an analysis of differential expression. The DESeqDataSet class enforces non-negative integer values in the "counts" matrix stored as the first element in the assay list. In addition, a formula which specifies the design of the experiment must be provided. The constructor functions create a DESeqDataSet object from various types of input: a RangedSummarizedExperiment, a matrix, count files generated by the python package HTSeq, or a list from the tximport function in the tximport package. See the vignette for examples of construction from different types.
This constructor function would not typically be used by "end users". This simple class extends the DataFrame class of the IRanges package to allow other packages to write methods for results objects from the DESeq2 package. It is used by results to wrap up the results table.
This constructor function would not typically be used by "end users". This simple class extends the RangedSummarizedExperiment class of the SummarizedExperiment package. It is used by rlog and varianceStabilizingTransformation to wrap up the results into a class for downstream methods, such as plotPCA.
coef
(Package: DESeq2) :
Extract a matrix of model coefficients/standard errors
Note: results tables with log2 fold change, p-values, adjusted p-values, etc. for each gene are best generated using the results function. The coef function is designed for advanced users who wish to inspect all model coefficients at once.
collapseReplicates
(Package: DESeq2) :
Collapse technical replicates in a RangedSummarizedExperiment or DESeqDataSet
Collapses the columns in object by summing within levels of a grouping factor groupby. The purpose of this function is to sum up read counts from technical replicates to create an object with a single column of read counts for each sample. Optionally renames the columns of returned object with the levels of the grouping factor. Note: this function is written very simply and can be easily altered to produce other behavior by examining the source code.
counts
(Package: DESeq2) :
Accessors for the 'counts' slot of a DESeqDataSet object.
The counts slot holds the count data as a matrix of non-negative integer count values, one row for each observational unit (gene or the like), and one column for each sample.
dispersionFunction
(Package: DESeq2) :
Accessors for the 'dispersionFunction' slot of a DESeqDataSet object.
The dispersion function is calculated by estimateDispersions and used by varianceStabilizingTransformation. Parametric dispersion fits store the coefficients of the fit as attributes in this slot.
providing 
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