norm_to_max: Normalize rows to the maximum value
In tkostas/komics: Tools to analyze omics data

Reads rows and normalized the values based on the maximum of the row (range 0-1).

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norm_to_max(x, columns = "..all..", label = "nmax_",
  complete_match = FALSE, sub_min = TRUE, na.rm = TRUE,
  drop_input = FALSE)

`x`	A dataframe with the values to be normalized.
`columns`	Vector containing column names to be standardized. By default all columns will be selected `"..all.."`. You can add a vector with the column names, or a part of the column name that is unique and use partial matching to identify columns (e.g. "values_"). If complete matching is used, specify `complete_match` argument to TRUE.
`label`	Label tag to be added in each collumn. Default value is "nmax_".
`complete_match`	Logical with default value `FALSE` that allows partial matching of the column names for selection of the column for normalizaiton. If set to `TRUE`, columns that match exactly with the input will be used.
`sub_min`	Logical with default value `TRUE`. By default the calculation is `(x - x_min) / (x_max - x_min)`. If `sub_min` is set to `FALSE` the normalization will be performed as: `x / x_max`
`na.rm`	Action for missing values when calculating min and max values. Defalut is `TRUE`
`drop_input`	Select if you want to append the normalized data into the input dataframe or keep only them. Logical with default value `FALSE`, meaning that the processed values will be added to the input.

data <- data.frame(L1 = c("a", "b", "c", "d", "e", "f", "g", "h"),
                   V1 = c(1, 2, 3, 6, 1, 3, 4, 4),
                   V2 = c(3, 4, 5, 3, 5, 5, 3, 2),
                   V3 = c(6, 7, 4, 2, 3, 2, 7, 6))
 norm_to_max(data, columns = "V")
 norm_to_max(data, columns = "V", sub_min = FALSE)