View source: R/nmr_normalize.R
nmr_normalize | R Documentation |
The nmr_normalize
function is used to normalize all the samples according
to a given criteria.
nmr_normalize(
samples,
method = c("area", "max", "value", "region", "pqn", "none"),
...
)
nmr_normalize_extra_info(samples)
samples |
A nmr_dataset_1D object |
method |
The criteria to be used for normalization - area: Normalize to the total area - max: Normalize to the maximum intensity - value: Normalize each sample to a user defined value - region: Integrate a region and normalize each sample to that region - pqn: Use Probabalistic Quotient Normalization for normalization - none: Do not normalize at all |
... |
Method dependent arguments:
- |
The aim is to correct from changes between samples, so no matter the criteria used to normalize, once we get the factors (e.g. the areas), we divide them by the median normalization factor to avoid introducing global scaling factors.
The nmr_normalize_extra_info
function is used to extract additional information
after the normalization. Typically, we want to know what was the actual normalization
factor applied to each sample. The extra information includes a plot, representing
the dispersion of the normalization factor for each sample.
The nmr_dataset_1D object, with the samples normalized.
Further information for diagnostic of the normalization process is also saved
and can be extracted by calling nmr_normalize_extra_info()
afterwards.
Other basic functions:
nmr_exclude_region()
nmr_dataset <- nmr_dataset_load(system.file("extdata", "nmr_dataset.rds", package = "AlpsNMR"))
nmr_dataset <- nmr_normalize(nmr_dataset, method = "area")
norm_dataset <- nmr_normalize(nmr_dataset)
norm_dataset$plot
nmr_dataset <- nmr_dataset_load(system.file("extdata", "nmr_dataset.rds", package = "AlpsNMR"))
nmr_dataset <- nmr_normalize(nmr_dataset, method = "area")
norm_extra_info <- nmr_normalize_extra_info(nmr_dataset)
norm_extra_info$plot
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