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T-test for Differential Expression Analysis

gly_ttest.Rd

Perform independent or paired t-tests for glycomics or glycoproteomics data. P-values are adjusted for multiple testing using the method specified by p_adj_method.

Usage

gly_ttest(
  exp,
  group_col = "group",
  p_adj_method = "BH",
  ref_group = NULL,
  add_info = TRUE,
  ...,
  subject_col = NULL,
  log_transform = TRUE
)

Arguments

exp

A glyexp::GlycomicSE() or glyexp::GlycoproteomicSE() object, or another SummarizedExperiment containing an expression matrix and sample information.

group_col

A character string specifying the column name of the grouping variable in the sample information. Default is "group".

p_adj_method

A character string specifying the method to adjust p-values. See p.adjust.methods for available methods. Default is "BH". If NULL, no adjustment is performed.

ref_group

A character string specifying the reference group. If NULL (default), the first level of the group factor is used as the reference.

add_info

A logical value. If TRUE (default), variable information from the experiment will be added to the result tibble. If FALSE, only the statistical results are returned.

...

Additional arguments passed to stats::t.test().

subject_col

An optional character string naming the subject identifier column in sample information. When supplied, samples are matched by subject and a paired t-test is performed.

log_transform

A single non-missing logical value. If TRUE (default), transform expression values using log2(x + 1e-6) before analysis. If FALSE, use the supplied values unchanged, for example for already log-transformed data.

Value

A list with three elements:

  • tidy_result: A tibble with t-test results containing the following columns:

    • variable: Variable name

    • estimate: Difference in group means (group2 - group1)

    • estimate1: Mean of group 1

    • estimate2: Mean of group 2

    • statistic: t-statistic

    • p_val: Raw p-value from t-test

    • parameter: Degrees of freedom

    • conf_low: Lower bound of 95% confidence interval

    • conf_high: Upper bound of 95% confidence interval

    • effect_size: Cohen's d, or Cohen's dz for paired analyses

    • method: Statistical method used

    • alternative: Alternative hypothesis

    • p_adj: Adjusted p-value (if p_adj_method is not NULL)

    • log2fc: Log2 fold change (log2(group2_mean / group1_mean))

  • raw_result: A list of t.test model objects

  • meta_data: A list containing metadata from the input experiment The list has classes glystats_ttest_res and glystats_res.

Details

Tests and effect sizes use the selected analysis scale. Reported fold changes continue to use ratios of group means from the original supplied values.

By default, expression data are transformed using log2(x + 1e-6) before statistical testing. Set log_transform = FALSE to skip this transformation. Exactly 2 groups are required in the grouping variable. In paired analyses, only subjects observed in both groups are used and effect_size is Cohen's \(d_z\) based on within-subject differences.

See also

stats::t.test()