rc.feature.filter.cv: rc.feature.filter.cv

In cbroeckl/RAMClustR: Mass Spectrometry Metabolomics Feature Clustering and Interpretation

rc.feature.filter.cv

Description

extractor for xcms objects in preparation for clustering

Usage

rc.feature.filter.cv(ramclustObj = NULL, qc.tag = "QC", max.cv = 0.5)

Arguments

ramclustObj	ramclustObj containing MSdata with optional MSMSdata (MSe, DIA, idMSMS)
qc.tag	character vector of length one or two. If length is two, enter search string and factor name in $phenoData slot (i.e. c("QC", "sample.type"). If length one (i.e. "QC"), will search for this string in the 'sample.names' slot by default.
max.cv	numeric maximum allowable cv for any feature. default = 0.5

Details

This function offers normalization by total extracted ion signal. it is recommended to first run 'rc.feature.filter.blanks' to remove non-sample derived signal.

Value

ramclustR object with total extracted ion normalized data.

Author(s)

Corey Broeckling

References

Broeckling CD, Afsar FA, Neumann S, Ben-Hur A, Prenni JE. RAMClust: a novel feature clustering method enables spectral-matching-based annotation for metabolomics data. Anal Chem. 2014 Jul 15;86(14):6812-7. doi: 10.1021/ac501530d. Epub 2014 Jun 26. PubMed PMID: 24927477.

cbroeckl/RAMClustR documentation built on Sept. 1, 2024, 1:50 a.m.