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Aggregates top N intensities

Source: R/tidyMS_aggregation.R
aggregate_intensity_top_n.Rd

run rank_peptide_by_intensity first

Usage

aggregate_intensity_top_n(ranked_data, lfqdata, .func, N = 3)

Arguments

ranked_data

data.frame with ranked peptides

lfqdata

LFQData object

.func

function to use for aggregation

N

default 3 top intensities.

Value

list with data and new reduced configuration (config)

See also

Other aggregation: INTERNAL_FUNCTIONS_BY_FAMILY, estimate_intensity(), medpolish_estimate(), medpolish_estimate_df(), medpolish_estimate_dfconfig(), plot_estimate(), plot_hierarchies_add_quantline(), plot_hierarchies_line(), plot_hierarchies_line_df(), rlm_estimate(), rlm_estimate_dfconfig()

Examples


dd <- prolfqua::sim_lfq_data_peptide_config()
#> creating sampleName from file_name column
#> completing cases
#> completing cases done
#> setup done
lfq <- LFQData$new(dd$data, dd$config)
ranked <- rank_peptide_by_intensity(lfq$get_data(), lfq$response(), lfq$hierarchy_keys())
#> Joining with `by = join_by(protein_Id, peptide_Id)`
#> Columns added : srm_meanInt srm_meanIntRank

mean_f <- function(x, name = FALSE) {
  if (name) return("mean")
  mean(x, na.rm = TRUE)
}

resTOPN <- aggregate_intensity_top_n(ranked, lfq, .func = mean_f, N = 3)
stopifnot(names(resTOPN) %in% c("data", "config"))
lfq_agg <- LFQData$new(resTOPN$data, resTOPN$config)
tmpRob <- plot_estimate(lfq, lfq_agg, show.legend = TRUE)
stopifnot("ggplot" %in% class(tmpRob$plots[[4]]))