analyzeSpikein: Comparison quantification with the expected spike-in...
In plger/RNAontheBENCH: RNAontheBENCH - Benchmark of RNAseq quantification and DEA

Description Usage Arguments Value Examples

View source: R/function.analyzeSpikein.R

Loads and processes the RNAseq data before comparing it with the spike-in concentrations. Will produce a number of benchmarking plots and files in the current working directory.

1	analyzeSpikein(ANALYSIS_NAME, rnaseq = NULL, qt, fc.undetected = 1)

`ANALYSIS_NAME`	A string indicating the name of the analysis/pipeline. Will be used in filenames, plot titles, etc.
`rnaseq`	The path to the gene-level RNAseq expression matrix. If not given, will look for relevant files in the working directory. The expression matrix should have gene symbols in the first column/row.names, and sample names (e.g. 'AJ80' for the 12-samples dataset, "A_1" for SEQC, etc) as column headers.
`qt`	A string indicating the unit of the expression matrix (either "FPKM", "TPM" or "COUNTS").
`fc.undetected`	The foldchange to assign to undetected spike-ins (should be either 1 or NA, default 1)

Nothing, but produces many files in the working directory...

# first we create a directory and put the example quantification file in it:
data(exampledata)
dir.create("example")
write.table(exampleGeneLevel,"w12.genes.quant",sep="\t",quote=FALSE)
# then we run the function, giving a name to the analysis, 
# specifying the file and type of quantification:
analyzeSpikein("tophat.featureCount", "w12.genes.quant", qt="COUNTS")