find.level3features: Find Level 3 Features

In HuanLab/JPA:

Find Level 3 Features

Description

Extracts and dereplicates level 3 features in each sample, then adds them to the original feature table.

Usage

find.level3features(data, mz.tol = 10, mass.tol = 0.05, rt.tol = 60, level3.threshold = 2)

Arguments

data	"MSdata" object generated by functions "XCMS.featureTable" or "custom.featureTable".
mz.tol	Mass tolerance in ppm used to identify putative level 3 features. Default = 10.
mass.tol	Mass tolerance in daltons used to extract level 3 features. Default = 0.05.
rt.tol	Retention time in seconds used to extract level 3 features. Default = 60.
level3.threshold	Intensity threshold used to extract level 3 features. The level 3 feature's peak intensity must be higher than level3.threshold * average intensity to be valid. Default = 2.

Value

Returns an updated feature table in dataframe format that includes newly identified level 3 features. Also returns an updated XCMS object that is used by functions later in the IPA workflow.

Author(s)

Sam Shen, Jian Guo, Tao Huan

Examples

library(IPA)
dir = "X:/Users/Sam_Shen/IPAtest_20210330/singleDDA"
featureTable <- peak.picking(dir = dir, mz.tol = 10, ppm=10, peakwidth=c(5,20), mzdiff = 0.01,
                             snthresh = 6, integrate = 1, prefilter = c(3,100), noise = 100)
featureTable <- find.level3features(data = MSdata)

HuanLab/JPA documentation built on April 14, 2023, 12:53 p.m.