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compute median and standard deviation for each sample

Source: R/tidyMS_R6_TransitionCorrelations.R
get_robscales.Rd

compute median and standard deviation for each sample

Usage

get_robscales(data, config)

See also

Other preprocessing: INTERNAL_FUNCTIONS_BY_FAMILY, apply_to_response_matrix(), filter_proteins_by_peptide_count(), normalize_log2_robscale(), robust_scale(), scale_with_subset(), scale_with_subset_by_factors()

Examples



bb <- prolfqua::sim_lfq_data_peptide_config()
#> creating sampleName from fileName column
#> completing cases
#> completing cases done
#> setup done
conf <- bb$config
sample_analysis <- bb$data
pepIntensityNormalized <- transform_work_intensity(sample_analysis, conf, log2)
#> Column added : log2_abundance
s1 <- get_robscales(pepIntensityNormalized, conf)

res <- scale_with_subset(pepIntensityNormalized, pepIntensityNormalized, conf)
#> Joining with `by = join_by(sampleName, isotopeLabel, protein_Id, peptide_Id)`
s2 <- get_robscales(res$data, conf)
abs(mean(s1$mads) - mean(s2$mads)) < 0.1
#> [1] TRUE