limma_dge: Using 'limma_dge' for 'raw' and 'fpkm' counts

In openanalytics/ganalyse: Easy Analysis of RNASeq DE

Description

limma_dge uses the limma package for DGE analysis on fpkm_counts and raw_counts object, and optionally also directly on an ExpressionSet object.

Usage

limma_dge(x, ...)

## Default S3 method:
limma_dge(x, ...)

## S3 method for class 'ExpressionSet'
limma_dge(x, design, contrast, voom = FALSE, ...)

## S3 method for class 'fpkm_counts'
limma_dge(x, design, contrast, voom = FALSE, ...)

## S3 method for class 'raw_counts'
limma_dge(x, design, contrast, voom = TRUE, ...)

Arguments

x	An object of class fpkm_counts, raw_counts or ExpressionSet.
...	Additional arguments.
design	A design matrix. See construct_design.
contrast	Contrast to compute DGE for. See construct_contrasts.
voom	Logical. If TRUE, applies voom transformation. Default is FALSE. Only relevant for limma_dge method.

Value

An object of class dge consisting of top tables from running the corresponding limma_dge method.

Note

The term differential gene expression or DGE is not used in a restrictive manner and applies to genomic features in general, i.e., genes, transcripts, exons etc.

See Also

rnaseq, gather_counts show_counts edger_dge construct_design construct_contrasts write_dge as.dgelist as.eset volcano_plot density_plot

Examples

path = system.file("tests", package="ganalyse")

# ----- fpkm ----- # 
fpkm_path = file.path(path, "fpkm", "annotation.txt")
fpkm_obj = rnaseq(fpkm_path, format="fpkm", experiment="sample")
fpkm_counts = gather_counts(fpkm_obj, by="gene-id", log_base=2L)
fpkm_design = construct_design(fpkm_counts, ~ 0 + condition)
fpkm_contrasts = construct_contrasts(
                     design = fpkm_design, 
                     treatA.vs.control = conditiontreatA-conditioncontrol, 
                     treatB.vs.control = conditiontreatB-conditioncontrol
                 )
# DE genes between treatA and control
limma_dge(fpkm_counts, design=fpkm_design, 
             contrast=fpkm_contrasts[, "treatA.vs.control"])
# DE genes between treatB vs control
limma_dge(fpkm_counts, design=fpkm_design, 
             contrast=fpkm_contrasts[, "treatB.vs.control"])
# DE genes between any of the treatments
limma_dge(fpkm_counts, design=fpkm_design, contrast=fpkm_contrasts)

# ----- raw ----- # 
raw_path = file.path(path, "raw", "annotation.txt")
raw_obj = rnaseq(raw_path, format="raw", experiment="sample")
raw_counts = gather_counts(raw_obj, by="gene-id", threshold=1L)
raw_design = construct_design(raw_counts, ~ 0 + condition)
raw_contrasts = construct_contrasts(
                     design = raw_design, 
                     treatA.vs.control = conditiontreatA-conditioncontrol, 
                     treatB.vs.control = conditiontreatB-conditioncontrol
                 )
# DE genes between treatA and control
limma_dge(raw_counts, design=raw_design, 
             contrast=raw_contrasts[, "treatA.vs.control"])
# DE genes between treatB and control
limma_dge(raw_counts, design=raw_design, 
             contrast=raw_contrasts[, "treatB.vs.control"])
# DE genes between any of the treatments
limma_dge(raw_counts, design=raw_design, contrast=raw_contrasts)

openanalytics/ganalyse documentation built on May 24, 2019, 2:25 p.m.