test_diff: Differential enrichment test
In DEP: Differential Enrichment analysis of Proteomics data

Description Usage Arguments Value Examples

test_diff performs a differential enrichment test based on protein-wise linear models and empirical Bayes statistics using limma. False Discovery Rates are estimated using fdrtool.

1 2	test_diff(se, type = c("control", "all", "manual"), control = NULL, test = NULL, design_formula = formula(~0 + condition))

`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()`, normalize the data using `normalize_vsn()` and impute remaining missing values using `impute()`.
`type`	"control", "all" or "manual", The type of contrasts that will be tested. This can be all possible pairwise comparisons ("all"), limited to the comparisons versus the control ("control"), or manually defined contrasts ("manual").
`control`	Character(1), The condition to which contrasts are generated if type = "control" (a control condition would be most appropriate).
`test`	Character, The contrasts that will be tested if type = "manual". These should be formatted as "SampleA_vs_SampleB" or c("SampleA_vs_SampleC", "SampleB_vs_SampleC").
`design_formula`	Formula, Used to create the design matrix.

A SummarizedExperiment object containing fdr estimates of differential expression.

# 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, normalize and impute missing values
filt <- filter_missval(se, thr = 0)
norm <- normalize_vsn(filt)
imputed <- impute(norm, fun = "MinProb", q = 0.01)

# Test for differentially expressed proteins
diff <- test_diff(imputed, "control", "Ctrl")
diff <- test_diff(imputed, "manual",
    test = c("Ubi4_vs_Ctrl", "Ubi6_vs_Ctrl"))

# Test for differentially expressed proteins with a custom design formula
diff <- test_diff(imputed, "control", "Ctrl",
    design_formula = formula(~ 0 + condition + replicate))