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