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Rank normalization methods by PC1 variance explained

Source: R/Normalization_Metrics.R
nm_rank_pc1.Rd

Computes the percentage of total variance captured by PC1 for each assay in a SummarizedExperiment and returns a data.frame sorted in descending order. Higher PC1 variance generally indicates stronger group separation.

Usage

nm_rank_pc1(
  se,
  assay_names = NULL,
  condition_col = "Condition",
  verbose = TRUE
)

Arguments

se

SummarizedExperiment from import_norm_matrices().

assay_names

Character vector of assay names to include. NULL = all.

condition_col

Column in colData with condition labels.

verbose

Logical. Print progress messages. Default TRUE.

Value

A data.frame with columns Method, PC1_VarPct, Rank, ordered by PC1_VarPct descending.

Examples

data(nadia_dia)
se <- nm_prepare_se(nadia_dia, verbose = FALSE)
se <- nm_run_normalizations(se, methods = c("cycloess", "quantile", "MAD"),
                            verbose = FALSE)

nm_rank_pc1(se, verbose = FALSE)
#>     Method PC1_VarPct Rank
#> 1 cycloess   72.57836    1
#> 2 quantile   65.48778    2
#> 3      MAD   64.86712    3
#> 4     log2   56.03859    4