FitGaussPeak {CorrectOverloadedPeaks} | R Documentation |

`FitGaussPeak`

will take retention time ('x') and intensity ('y') data and extrapolate all points above
a certain threshold based on further parameters using a Gaussian approach.

FitGaussPeak(x, y, scale_range = c(1, 10), steps = 10, cutoff = 0.95, idx = NULL, weight_front = 0.5, strip_data = "none", account_for_baseline_offset = TRUE, method = c("Gauss", "EMG")[1], silent = TRUE, fix_sd = NULL, ...)

`x` |
A numeric vector, retention times. |

`y` |
A numeric vector, ion intensities. |

`scale_range` |
Specifies the expected range for the true peak to exceed the observed, where scale_range=c(1,100) would assume anything between not overloaded and 100-fold overloaded. |

`steps` |
Specifies a step parameter used to create a sequence within 'scale_range' to test for good fits, higher=more precision, fewer=faster. |

`cutoff` |
Overloaded peaks will be screwed from gaussian shape already when approaching detector saturation (DS), cutoff=0.95 ensures that points just before DS will not be used to model fit. |

`idx` |
If not NULL, 'idx' is expected to specify points to correct explicitly (as a numeric-vector within 1:length(x)). |

`weight_front` |
A weighting parameter to punish deviations in peak front and tail differently; 0.5=use front/tail equally, 1=use only front, 0=use only tail. |

`strip_data` |
Use all provided data if 'none' (default). Strip 'front' or 'tail' data in case you observe peak fronting or tailing respectively. |

`account_for_baseline_offset` |
If TRUE will substract min(y) from y before fitting parameters. |

`method` |
The method for peak shape calculation. Can be 'Gauss' or 'EMG' (exponentially modified gauss). |

`silent` |
For testing purposes some QC-plot will be generated if silent=FALSE. |

`fix_sd` |
Supply a fix standard deviation (sd) for the peak or leave NULL to estimate sd within function. |

`...` |
passed to the QC plot function, e.g. 'main' or 'xlab'. |

This function is mainly used internally (`CorrectOverloadedPeaks`

) but can be of value on it's
own to test brute force peak reconstruction given that appropriate base peak chromatograms are available.

An annotated plot of the mass spectrum and detailed information within the console (if silent=FALSE) and the optimal fitted data points (vector of length(y), returned invisible).

#load test data data("mzXML_data") names(mzXML_data) str(mzXML_data[["scan"]][[1]]) pk <- ModelGaussPeak(height=10^7, width=3, scan_rate=10, e=0, ds=8*10^6, base_line=10^2) plot(pk, main="Gaussian peak of true intensity 10^7 but cutt off at 8*10^6") idx <- pk[,"int"]>0.005 * max(pk[,"int"]) tmp <- FitGaussPeak(x=pk[idx,"rt"], y=pk[idx,"int"], silent=FALSE, xlab="RT", ylab="Intensity")

[Package *CorrectOverloadedPeaks* version 1.2.17 Index]