calc_log2_df: Calculate log2 values in a dataframe
In tkostas/komics: Tools to analyze omics data

Reads a data-frame and calculates log2 for each value. Non-numeric columns that should be transformed can be excluded by adding the column name in exclusion vector. For partial matching of column names use complete_match = FALSE. Transformed columns can be renamed using the log_lab argument. Missing values can be either replaced with 0 or removed by adjusting the rm_zero argument.

1 2	calc_log2_df(x, log_lab, rm_zero = TRUE, exclusion = c(), complete_match = TRUE, append = FALSE)

`x`	Dataframe containing only numeric values.
`log_lab`	Character tag to be added in front of every column name of the dataframe (e.g. "Log2_".
`rm_zero`	If `TRUE`, missing values will remain `NA`. If set to `FALSE` missing values will be replaced by 0. By default `rm_zero = TRUE`.
`exclusion`	Vector containing labels from the columns that should be excluded. Even a part of the label is enough.
`complete_match`	Logical with default value `TRUE`. If exclusion vector contains exactly the column names of the excluded columns, leave the `complete_match` to `TRUE`. For partial matching of the columns switch to `FALSE`
`append`	Logical with default value `FALSE`. If set `TRUE` processed data will be added in the starting dataframe. If `FALSE`, the processed columned will be merged only with the excluded ones.