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Analyzing summarized data

Source: R/analyze.R
analyze.Rd

Apply a statistical test to the data.

Usage

analyze(
  dataSet,
  testType = "t-test",
  ref = NULL,
  paired = FALSE,
  pool.sd = FALSE
)

Arguments

dataSet

The 2d data set of data.

testType

A string (default = "t-test") specifying which statistical test to use:

  1. "t-test": Student's t-test.

  2. "mod.t-test": Empirical Bayes moderated t-test (Smyth 2004) .

  3. "wilcox-test": Wilcoxon test.

  4. "MA": Output to plot an MA plot.

ref

A string (default = NULL) specifying the reference condition for comparison. If NULL, all pairwise comparisons are performed.

paired

A boolean (default = FALSE) specifying whether or not to perform a paired test when testType = "t-test" or testType = "wilcox-test".

pool.sd

A boolean (default = FALSE) specifying whether or not to use a pooled standard deviation when testType = "t-test".

Value

  • "t-test", "mod.t-test", "wilcox-test": A list comprising data frames for each comparison, with each data frame containing the means of the two compared conditions for each protein, the difference in means, and the p-values. Additionally, a separate data frame called "total" summarizes the results of multiple comparisons.

  • "MA": A list comprising data frames for each comparison, with each data frame containing the means of the two compared conditions for each protein, as well as the average and difference in means.

References

Smyth GK (2004). “Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments.” Statistical Applications in Genetics and Molecular Biology, 3(1). doi:10.2202/1544-6115.1027 .