Description Usage Arguments Details Value Author(s) Examples

It computes the estimated X abundances of each sample,
returning an object of the class `labelling`

.

1 2 | ```
main_labelling(peak_table, compound, charge = 1, labelling, mass_shift, RT,
RT_shift, chrom_width, initial_abundance = NA)
``` |

`peak_table` |
A data.frame containing the integrated signals for the samples |

`compound` |
The chemical formula of the compound of interest |

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

`labelling` |
Character, either "H" or "C", specifying which is the labelling element |

`mass_shift` |
Maximum shift allowed in the mass range |

`RT` |
Expected retention time of the compund of interest |

`RT_shift` |
Maximum shift allowed in the retention time range |

`chrom_width` |
Chromatographic width of the peaks |

`initial_abundance` |
Initial estimate for the abundance of the heaviest X isotope (the label) |

peak_table: The first two columns of

`peak_table`

represent the mass and the retention time of the peaks; the other columns represent peak intensities for each sample. The table can be obtained using the function`table_xcms`

compound: Character vector, where X has to represent the element with isotopic distribution to be fitted

initial_abundance: Numeric vector of the same length as the number of samples, with the initial estimate for the abundance of the heaviest X isotope (either ^2H or ^13C). If provided, number between 0 and 100. Otherwise, NA

An object of the class `labelling`

, which is a list containing the results from 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 representing the best estimated abundance of the heaviest X isotope (either ^2H or ^13C). Number between 0 and 100 |

`std_error` |
Numeric vector containing the standard errors of the estimates |

`dev_percent` |
The percentage deviations of the fitted theoretical patterns to the provided experimental patterns |

`x_scale` |
Vector containing the |

`y_exp` |
Matrix containing normalised experimental patterns, where for each sample the most intense signal is set to 100 |

`y_theor` |
Matrix of normalised fitted theoretical pattern (most intense signal set to 100 for each sample) |

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

`warnings` |
Character vector containing possible warnings coming from the fitting procedure |

Ruggero Ferrazza

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | ```
data(xcms_obj)
peak_table <- table_xcms(xcms_obj)
fitted_abundances <- main_labelling(peak_table,
compound="X40H77NO8P",
charge=1,
labelling="C",
mass_shift=0.05,
RT=285,
RT_shift=20,
chrom_width=7,
initial_abundance=NA)
summary(object=fitted_abundances)
plot(x=fitted_abundances, type="patterns", saveplots=FALSE)
plot(x=fitted_abundances, type="residuals", saveplots=FALSE)
plot(x=fitted_abundances, type="summary", saveplots=FALSE)
save_labelling(fitted_abundances)
grouped_estimates <- group_labelling(fitted_abundances,
groups=factor(c(rep("C12",4),
rep("C13",4))))
# Other possible lipid compounds include:
# [PC34:1 + H]+. compound="X42H83NO8P", RT=475, chrom_width=10
# [TAG47:3 + NH4]+(a minor species). compound="X50H94NO6",
# RT=891, chrom_width=7
``` |

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