getPeakQualityMetrics: Calculate the 12 Peak Quality Metrics

In KelseyChetnik/MetaClean: Detection of Low-Quality Peaks in Untargeted Metabolomics Data

Description

Wrapper function for calculating the each of the 12 peak quality metrics for each feature.

Usage

getPeakQualityMetrics(eicEvalData, eicLabels_df, flatness.factor = 0.05)

Arguments

eicEvalData	An object of class evalObj containing the required chromatographic peak information
eicLabels_df	A dataframe with EICNos in the first column and Labels in the second column
flatness.factor	A numeric value between 0 and 1 that allows the user to adjust the sensitivity of the function to noise. This function calculates the difference between each adjacent pair of points; any value found to be less than flatness.factor * maximum intensity is set to 0.

Value

An Mx14 matrix where M is equal to the number of peaks. There are 14 columns in total, including one column for each of the twelve metrics, one column for EIC numbers, and one column for the class label.

Examples

# # calculate peak quality metrics for development dataset
pqMetrics_development <- getPeakQualityMetrics(eicEvalData = eicEval_development,
eicLabels_df = eicLabels_development)

KelseyChetnik/MetaClean documentation built on May 17, 2021, 5:33 a.m.