This function will automatically scale your data based on the normalization method you choose. It will also calculate the CVs for each sample and each metabolite.
Usage
auto_scale(
data,
sample_information,
is_to_use = "",
pref_to_use = "PREFA",
prefs_to_remove = "",
normalization = c("IS", "NN"),
pool_missing_p = 100,
fill_method = "none",
smooth_method = "lowess"
)Arguments
- data
A data frame of the data to be normalized. This should be the output of the
read_datafunction.- sample_information
A data frame of the sample information. This should be the output of the
read_sample_informationfunction.- is_to_use
A vector of the internal standards to use for normalization. If you do not want to use internal standards, leave this blank.
- pref_to_use
A string of the preferred reference to use for normalization. If you do not want to use a preferred reference, leave this blank.
- prefs_to_remove
A vector of the preferred references to remove from the data. If you do not want to remove any preferred references, leave this blank.
- normalization
A string of the normalization method to use. This can be "IS", "NN", or "SMOOTH".
- pool_missing_p
A numeric value indicating the percentage of missing pools allowed before skipping normalization (0-100).
- fill_method
A string indicating how to fill missing values. This can be "half-min" or "none".
- smooth_method
A string indicating the smoothing method to use. This can be "lowess", "line", "spline", or "gaussian".