| rc.feature.filter.cv {RAMClustR} | R Documentation |
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.