This package implements a set of utility functions to enable a
limma/voom workflow capturing the results in the DGEobj data structure.
Aside from implementing a well developed and popular workflow in DGEobj
format, the run* functions in the package illustrate how to wrap the
individual processing steps in a workflow in functions that capture
important metadata, processing parameters, and intermediate data items
in the DGEobj data structure. This function- based approach to utilizing
the DGEobj data structure insures consistency among a collection of
projects processed by these methods and thus facilitates downstream
automated meta-analysis.

### Functionality includes:

#### Analysis

**runContrasts**: Build contrast matrix and calculate
contrast fits
**runEdgeRNorm**: Run edgeR normalization on
DGEobj
**runIHW**: Apply Independent Hypothesis Weighting
(IHW) to a list of topTable dataframes
**runPower**: Run a power analysis on counts and design
matrix
**runQvalue**: Calculate and add q-value and lFDR to
dataframe
**runSVA**: Test for surrogate variables
**runVoom**: Run functions in a typical voom/lmFit
workflow

#### Utilities

**convertCounts**: Convert count matrix to CPM, FPKM,
FPK, or TPM
**extractCol**: Extract a named column from a series of
df or matrices
**lowIntFilter**: Apply low intensity filters to a
DGEobj
**rsqCalc**: Calculate R-squared for each gene fit
**summarizeSigCounts**: Summarize a contrast list
**topTable.merge**: Merge specified topTable df
cols
**tpm.direct**: Convert countsMatrix and geneLength to
TPM units
**tpm.on.subset**: Calculate TPM for a subsetted
DGEobj