Total ion count normalization
Arguments
- data
DF which contains unique sample identifiers as row names and metabolite numerical values in columns with metabolite identifiers as column names. Use NA for metabolites that were not detected and consider converting any zeros to NA unless they are true zeros.
- metadata_sample
DF which contains information about the samples, which will be combined with the input data based on the unique sample identifiers used as rownames.
- metadata_info
Named vector containing the information about the names of the experimental parameters. c(Conditions="ColumnName_Plot_SettingsFile").
- tic
Optional: If TRUE, total Ion Count normalization is performed. If FALSE, only RLA QC plots are returned. Default = TRUE
Value
List with two elements: DF (including output table) and Plot (including all plots generated)
This function can be used independently on numeric data with matching sample metadata. Missing values and zero handling should already be in a reasonable state for the intended normalization.
Examples
data(intracell_raw)
Intra <- intracell_raw %>% tibble::column_to_rownames("Code")
Res <- tic_norm(
data =
Intra[-c(49:58), -c(1:3)] %>%
dplyr::mutate_all(
~ ifelse(grepl("^0*(\\.0*)?$", as.character(.)), NA, .)
),
metadata_sample = Intra[-c(49:58), c(1:3)],
metadata_info = c(Conditions = "Conditions")
)
#> total Ion Count (tic) normalization: total Ion Count (tic) normalization is used to reduce the variation from non-biological sources, while maintaining the biological variation. REF: Wulff et. al., (2018), Advances in Bioscience and Biotechnology, 9, 339-351, doi:https://doi.org/10.4236/abb.2018.98022
#> Warning: Removed 39 rows containing non-finite outside the scale range
#> (`stat_boxplot()`).
#> Warning: Removed 39 rows containing non-finite outside the scale range
#> (`stat_boxplot()`).