adjustData: Process and Filter Metabolomics Feature Lists

In metabCombiner: Method for Combining LC-MS Metabolomics Feature Measurements

Description

adjustData contains a set of pre-analysis steps for processing LC-MS metabolomics feature tables individually

Usage

adjustData(Data, misspc, measure, rtmin, rtmax, zero, duplicate)

Arguments

Data	a metabData object.
misspc	Numeric. Threshold missingness percentage for analysis.
measure	Character. Choice of central abundance measure; either "median" or "mean".
rtmin	Numeric. Minimum retention time for analysis.
rtmax	Numeric. Maximum retention time for analysis.
zero	Logical. Whether to consider zero values as missing.
duplicate	Ordered numeric pair (m/z, rt) tolerance parameters for duplicate feature search.

Details

The pre-analysis adjustment steps include: 1) Restriction to a feature retention time range rtmin ≤ rt ≤ rtmax 2) Removal of features with a percent missingness exceeding misspc 3) Removal of duplicate metabolomics features.

After processing, abundance quantile (Q) values are calculated between 0 & 1 for the remaining features, as ranked by the measure argument, unless provided by the user.

Value

Updated metabData object. The data field is processed by the listed steps and stats list updated to contain feature statistics.

See Also

metabData: the constructor for metabData objects, filterRT: function for filtering by retention times, findDuplicates: function for finding duplicates

metabCombiner documentation built on Dec. 10, 2020, 2 a.m.