normalize_vsn: Normalization using vsn
In arnesmits/DEP: Differential Enrichment analysis of Proteomics data

Description Usage Arguments Value Examples

normalize_vsn performs variance stabilizing transformation using the vsn-package.

1	normalize_vsn(se)

`se`	SummarizedExperiment, Proteomics data (output from `make_se()` or `make_se_parse()`). It is adviced to first remove proteins with too many missing values using `filter_missval()`.

A normalized SummarizedExperiment object.

# Load example
data <- UbiLength
data <- data[data$Reverse != "+" & data$Potential.contaminant != "+",]
data_unique <- make_unique(data, "Gene.names", "Protein.IDs", delim = ";")

# Make SummarizedExperiment
columns <- grep("LFQ.", colnames(data_unique))
exp_design <- UbiLength_ExpDesign
se <- make_se(data_unique, columns, exp_design)

# Filter and normalize
filt <- filter_missval(se, thr = 0)
norm <- normalize_vsn(filt)