test_diff {DEP} | R Documentation

## Differential enrichment test

### Description

`test_diff` performs a differential enrichment test based on protein-wise linear models and empirical Bayes statistics using limma.

### Usage

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

### Arguments

`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.

### Value

A SummarizedExperiment object containing FDR estimates of differential expression.

### Examples

    # 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))

[Package DEP version 1.2.0 Index]