limma_pipe: Pipeline for limma+voom analysis
In anilchalisey/parseR: Pipeline for Analysis of RNA-seq in R

Function to perform entire limma+voom analysis using voom with quality weights, and beginning with a SummarizedExperiment and ending with list of differential genes and generation of diagnostic plots along the way.

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limma_pipe(se = NULL, design = NULL, contrast = NULL,
  block.column = NULL, norm.method = "TMM", adjust.method = "BH",
  p.value = 0.05)

`se`	SummarizedExperiment with an assay slot named counts_fil containing the filtered counts and colData slot containing sample metadata.
`design`	A design matrix specifying the experimental design. If NULL, then a design matrix will be created using the values for contrast.levels and block.levels.
`contrast`	A matrix of contrasts (as created by `makeContrasts` in the `limma` package specifying the comparisons to perform). If NULL, then will be created from the design matrix.
`block.column`	The column in the samples metadata dataframe specifying the block/additive effect column. Ignored if design is not NULL.
`norm.method`	Normalisation method to use - may be "TMM", "RLE", "upperquartile" or "none".
`adjust.method`	Method to be used for adjustment of nominal p-values. May be one of "BH", "bonferroni", "holm", "hochberg", "hommel", "BY".
`p.value`	Value between 0 and 1. Adjusted p-value for the differential expression analysis.