View source: R/tidyMS_R6_TransitionCorrelations.R
get_robscales | R Documentation |
compute median and standard deviation for each sample
get_robscales(data, config)
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()
bb <- prolfqua::sim_lfq_data_peptide_config()
conf <- bb$config
sample_analysis <- bb$data
pepIntensityNormalized <- transform_work_intensity(sample_analysis, conf, log2)
s1 <- get_robscales(pepIntensityNormalized, conf)
res <- scale_with_subset(pepIntensityNormalized, pepIntensityNormalized, conf)
s2 <- get_robscales(res$data, conf)
abs(mean(s1$mads) - mean(s2$mads)) < 0.1
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