transform_raw_data: Functions to log transform raw data before normalization and...
In proBatch: Tools for Diagnostics and Corrections of Batch Effects in Proteomics

Description Usage Arguments Value Examples

Functions to log transform raw data before normalization and batch correction

Log transformation of the data

"Unlog" transformation of the data to pre-log form (for quantification, forcing log-transform)

log_transform_df(df_long, log_base = 2, offset = 1, measure_col = "Intensity")

unlog_df(df_long, log_base = 2, offset = 1, measure_col = "Intensity")

log_transform_dm(data_matrix, log_base = 2, offset = 1)

unlog_dm(data_matrix, log_base = 2, offset = 1)

`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.
`log_base`	base of the logarithm for transformation
`offset`	small positive number to prevent 0 conversion to `-Inf`
`measure_col`	if `df_long` is among the parameters, it is the column with expression/abundance/intensity; otherwise, it is used internally for consistency.
`data_matrix`	features (in rows) vs samples (in columns) matrix, with feature IDs in rownames and file/sample names as colnames. See "example_proteome_matrix" for more details (to call the description, use `help("example_proteome_matrix")`)

'log_transform_df()' returns df_long-size data frame, with measure_col log transformed; with old value in another column called "beforeLog_intensity" if "intensity" was the value of measure_col; 'log_transform_dm()' returns data_matrix format matrix

log_transformed_df <- log_transform_df(example_proteome)

log_transformed_matrix <- log_transform_dm(example_proteome_matrix, 
log_base = 10, offset = 1)