calculate_feature_CV: Calculate CV distribution for each feature

In proBatch: Tools for Diagnostics and Corrections of Batch Effects in Proteomics

Description

Calculate CV distribution for each feature

Usage

calculate_feature_CV(
  df_long,
  sample_annotation = NULL,
  feature_id_col = "peptide_group_label",
  sample_id_col = "FullRunName",
  measure_col = "Intensity",
  batch_col = NULL,
  biospecimen_id_col = NULL,
  unlog = TRUE,
  log_base = 2,
  offset = 1
)

Arguments

df_long	data frame where each row is a single feature in a single sample. It minimally has a sample_id_col, a feature_id_col and a measure_col, but usually also an m_score (in OpenSWATH output result file). See help("example_proteome") for more details.
sample_annotation	data frame with: sample_id_col (this can be repeated as row names) biological covariates technical covariates (batches etc) . See help("example_sample_annotation")
feature_id_col	name of the column with feature/gene/peptide/protein ID used in the long format representation df_long. In the wide formatted representation data_matrix this corresponds to the row names.
sample_id_col	name of the column in sample_annotation table, where the filenames (colnames of the data_matrix are found).
measure_col	if df_long is among the parameters, it is the column with expression/abundance/intensity; otherwise, it is used internally for consistency.
batch_col	column in sample_annotation that should be used for batch comparison (or other, non-batch factor to be mapped to color in plots).
biospecimen_id_col	column in sample_annotation that defines a unique bio ID, which is usually a combination of conditions or groups. Tip: if such ID is absent, but can be defined from several columns, create new biospecimen_id column
unlog	(logical) whether to reverse log transformation of the original data
log_base	base of the logarithm for transformation
offset	small positive number to prevent 0 conversion to -Inf

Value

data frame with Total CV for each feature & (optionally) per-batch CV

Examples

CV_df = calculate_feature_CV(example_proteome, 
sample_annotation = example_sample_annotation, 
measure_col = 'Intensity', 
batch_col = 'MS_batch')

proBatch documentation built on Nov. 8, 2020, 4:55 p.m.