lfq_power_t_test_proteins: Compute theoretical sample sizes from factor level standard...

In wolski/prolfqua: Proteomics Label Free Quantification

Compute theoretical sample sizes from factor level standard deviations

Description

Compute theoretical sample sizes from factor level standard deviations

Usage

lfq_power_t_test_proteins(
  stats_res,
  delta = c(0.59, 1, 2),
  power = 0.8,
  sig.level = 0.05,
  min.n = 1.5
)

Arguments

stats_res	data.frame 'summarize_stats' output
delta	effect size you are interested in
power	of test
min.n	smallest n to determine
sigma.level	P-Value

See Also

Other stats: INTERNAL_FUNCTIONS_BY_FAMILY, lfq_power_t_test_quantiles(), lfq_power_t_test_quantiles_V2(), plot_stat_density(), plot_stat_density_median(), plot_stat_violin(), plot_stat_violin_median(), plot_stdv_vs_mean(), pooled_V2(), summarize_stats()

Examples

bb1 <- prolfqua::sim_lfq_data_peptide_config()

ldata <- LFQData$new(bb1$data, bb1$config)
stats_res <- summarize_stats(ldata$data, ldata$config)
bb <- lfq_power_t_test_proteins(stats_res)

wolski/prolfqua documentation built on May 12, 2024, 10:16 p.m.