find_abundance: Fit experimental isotopic patterns

Description Usage Arguments Value Author(s) See Also Examples

Description

Function that takes each of the provided experimental MS isotopic patterns, and fits the best theoretical pattern that reproduces it through a weighted non-linear least squares procedure.

Usage

1
find_abundance(patterns, info, initial_abundance = NA, charge = 1)

Arguments

patterns

A matrix of experimental isotopic patterns (one column for each sample), with the first two columns representing m/z and retention time of the corresponding peaks

info

Named list containing isotopic information, output of the isotopic_information function

initial_abundance

Either NA, or a numeric vector of length equal to the number of samples, with the initial guesses on the percentage isotopic abundance of the labelling isotope (denoted as X, it can be either ^2H or ^13C). If provided, numbers between 0 and 100

charge

Natural number, denoting the charge state of the target adduct (1,2,3,...). If not provided, it is 1 by default

Value

An object of class labelling, which is a list containing the results of the fitting procedure:

compound

Character vector specifying the chemical formula of the compound of interest, with X being the element with unknown isotopic distribution (to be fitted)

best_estimate

Numeric vector of length equal to the number of samples, containing the estimated percentage abundances of the labelling isotope X (either ^2H or ^13C). Numbers between 0 and 100

std_error

Numeric vector with the standard errors of the estimates, output of the nls fitting procedure

dev_percent

Numeric vector with the percentage deviations between best fitted and related experimental patterns

x_scale

Numeric vector containing the m/z values relative to the signals of the experimental patterns

y_exp

Matrix of normalised experimental isotopic patterns (one column for each sample). The most intense signal of each pattern is set to 100

y_theor

Matrix of normalised fitted theoretical isotopic patterns (one column for each sample). The most intense signal of each pattern is set to 100

residuals

Matrix of residuals: each column is the difference between experimental and best fitted theoretical patterns

warnings

Character vector with possible warnings from the nls fitting procedure

Author(s)

Ruggero Ferrazza

See Also

isotopic_information

Examples

1
2
3
4
## Not run: 
fitted_abundances <- find_abundance(patterns, info, initial_abundance=NA, charge=1)

## End(Not run)

RuggeroFerrazza/IsotopicLabeling documentation built on May 9, 2019, 10:36 a.m.