Compute mean, sd, and CV for all Peptides, or proteins, for all interactions and all samples.

Compute mean, sd, and CV for all Peptides, or proteins, for all interactions and all samples.

summarize stats output (compute quantiles)

Usage

summarize_stats(lfqdata, factor_key = lfqdata$relevant_factor_keys())

summarize_stats_quantiles(
  stats_res,
  factor_keys_depth,
  stats = c("sd", "CV"),
  probs = c(0.1, 0.25, 0.5, 0.75, 0.9)
)

Arguments

lfqdata

LFQData object

factor_key

character vector — factor columns to group by (default: relevant_factor_keys)

stats_res

result of running `summarize_stats`

factor_keys_depth

character vector — factor columns at current depth

stats

summarize either sd or CV

probs

for which quantiles 10, 20 etc.

See also

Other stats: INTERNAL_FUNCTIONS_BY_FAMILY, compute_pooled(), 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()

Other stats: INTERNAL_FUNCTIONS_BY_FAMILY, compute_pooled(), 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()

Examples

bb <- prolfqua::sim_lfq_data_protein_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)

res2 <- prolfqua::sim_lfq_data_2factor_config()
#> creating sampleName from file_name column
#> completing cases
#> completing cases done
#> setup done
res2$config$factor_depth <- 2
lfq2 <- LFQData$new(res2$data, res2$config)
stats <- summarize_stats(lfq2)
stopifnot(nrow(stats) == 40)

stats <- summarize_stats(lfq2, factor_key = lfq2$factor_keys()[1])
stopifnot(nrow(stats) == 20)
stats <- summarize_stats(lfq2, factor_key = lfq2$factor_keys()[2])
stopifnot(nrow(stats) == 20)
stats <- summarize_stats(lfq2, factor_key = NULL)
stopifnot(nrow(stats) == 10)
library(ggplot2)
bb1 <- prolfqua::sim_lfq_data_peptide_config()
#> creating sampleName from file_name column
#> completing cases
#> completing cases done
#> setup done
lfq <- LFQData$new(bb1$data, bb1$config)
stats_res <- summarize_stats(lfq)
sq <- summarize_stats_quantiles(stats_res, lfq$relevant_factor_keys())
sq <- summarize_stats_quantiles(stats_res, lfq$relevant_factor_keys(), stats = "CV")
sq <- summarize_stats_quantiles(stats_res, lfq$relevant_factor_keys(), stats = "sd")
xx <- summarize_stats_quantiles(stats_res, lfq$relevant_factor_keys(), probs = seq(0, 1, by = 0.1))
ggplot2::ggplot(xx$long, aes(x = probs, y = quantiles, color = group_)) + geom_line() + geom_point()