Scale using a subset of the data, within factor levels (e.g. use for pulldown data)

This method reduces the variance within the group.

scale_with_subset_by_factors(data, subset, config, preserveMean = FALSE)

Arguments

data

tibble with data

subset

tibble with subset of the data which will be used to derive scaling parameters

config

configuration

preserveMean

default FALSE then set mean to 0

See also

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

Examples

bb <- sim_lfq_data_peptide_config(Nprot = 100)
#> creating sampleName from fileName column
#> Warning: no nr_children column specified in the data, adding column nr_children and setting to 1.
#> completing cases
conf <- bb$config$clone(deep=TRUE)
sample_analysis <- bb$data

res <- transform_work_intensity(sample_analysis, conf, log2)
#> Column added : log2_abundance
res <- scale_with_subset_by_factors(res, res, conf)
#> Warning: Expected 2 pieces. Additional pieces discarded in 1400 rows [1, 2, 3, 4, 5, 6,
#> 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, ...].
#> Joining with `by = join_by(sampleName, protein_Id, peptide_Id)`
#> Warning: Expected 2 pieces. Additional pieces discarded in 1400 rows [1, 2, 3, 4, 5, 6,
#> 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, ...].
#> Joining with `by = join_by(sampleName, protein_Id, peptide_Id)`
#> Warning: Expected 2 pieces. Additional pieces discarded in 1400 rows [1, 2, 3, 4, 5, 6,
#> 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, ...].
#> Joining with `by = join_by(sampleName, protein_Id, peptide_Id)`