following the documentation here: https://online.stat.psu.edu/stat500/lesson/7/7.3/7.3.1/7.3.1.1
See also
Other stats:
INTERNAL_FUNCTIONS_BY_FAMILY,
lfq_power_t_test_proteins(),
lfq_power_t_test_quantiles_V2(),
plot_stat_density(),
plot_stat_density_median(),
plot_stat_violin(),
plot_stat_violin_median(),
plot_stdv_vs_mean(),
summarize_stats()
Other stats:
INTERNAL_FUNCTIONS_BY_FAMILY,
lfq_power_t_test_proteins(),
lfq_power_t_test_quantiles_V2(),
plot_stat_density(),
plot_stat_density_median(),
plot_stat_violin(),
plot_stat_violin_median(),
plot_stdv_vs_mean(),
summarize_stats()
Examples
x <- data.frame(nrMeasured =c(1,2,2), var = c(3,4,4), meanAbundance = c(3,3,3))
x <- data.frame(nrMeasured = c(1,2,1,1), var = c(NA, 0.0370, NA, NA),
meanAbundance = c(-1.94,-1.46,-1.87,-1.45))
compute_pooled(x)
#> n.groups n df sd sdT var mean meanAll nrMeasured
#> 1 1 2 1 0.1923538 0.1923538 0.037 -1.46 -1.636 5
y <- data.frame(dilution.=c("a","b","c"),
nrReplicates = c(4,4,4), nrMeasured = c(0,0,1), sd =c(NA,NA,NA),
var = c(NA,NA,NA),meanAbundance = c(NaN,NaN,NaN))
compute_pooled(y)
#> n.groups n df sd sdT var mean meanAll nrMeasured
#> 1 0 0 0 NaN NaN NaN NaN NaN 1
yb <- y |> dplyr::filter(nrMeasured > 1)
bb <- prolfqua::sim_lfq_data_peptide_config()
#> creating sampleName from file_name column
#> completing cases
#> completing cases done
#> setup done
lfq <- LFQData$new(bb$data, bb$config)
res1 <- summarize_stats(lfq)
pv <- poolvar(res1, bb$config)
stopifnot(nrow(pv) == nrow(res1) / 3)