medianquotientnorm: Median Quotient Normalization of glycan data
In glycanr: Tools for Analysing N-Glycan Data

Description Usage Arguments Details Value Author(s) References Examples

Returns glycans normalized with Median Quotient Normalization approach.

1	medianquotientnorm(d, grouping = FALSE)

`d`	data frame in long format containing glycan measurements
`grouping`	should data be normalized per groups

Input data frame should have at least the following three columns:
- gid - representing a unique name of a sample
- glycan - representing glycan names
- value - representing measured values
and if the grouping argument is TRUE it should also have column:
- groups - representing groupings (e.g. IgG1, IgG2 and IgG4)

Returns a data.frame with original glycan values substituted by normalized ones

Ivo Ugrina, Lucija Klarić

Dieterle F,Ross A, Schlotterbeck G, Senn H.:
Probabilistic Quotient Normalization as Robust Method to Account for Diluition of Complex Biological Mixtures. Application in 1H NMR Metabolomics.
Anal Chem 2006;78:4281-90.
doi: 10.1021/ac051632c

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data(mpiu)
mpiun <- medianquotientnorm(mpiu)
head(mpiun)

From version 0.3 functions tanorm and glyco.outliers expect data frames
in long format.
# A tibble: 6 x 4
  Plate   gid glycan      value
  <int> <chr> <fctr>      <dbl>
1     1   1_1    GP1   15871.55
2     1   1_1   GP10  745523.15
3     1   1_1   GP11  121467.70
4     1   1_1   GP12   95039.42
5     1   1_1   GP13   39350.21
6     1   1_1   GP14 2610145.83