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