| rc.restore.qc.samples {RAMClustR} | R Documentation |
rc.restore.qc.samples
Description
summarize quality control for clustering and for quality control sample variation based on compound ($SpecAbund) and feature ($MSdata and $MSMSdata, if present)
Usage
rc.restore.qc.samples(ramclustObj = NULL)
Arguments
ramclustObj |
ramclustR object to analyze |
Details
moves all of $phenoData, $MSdata, $MSMSdata, $SpecAbund back to original positions from $qc slot
Value
RC object
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.
Broeckling CD, Ganna A, Layer M, Brown K, Sutton B, Ingelsson E, Peers G, Prenni JE. Enabling Efficient and Confident Annotation of LC-MS Metabolomics Data through MS1 Spectrum and Time Prediction. Anal Chem. 2016 Sep 20;88(18):9226-34. doi: 10.1021/acs.analchem.6b02479. Epub 2016 Sep 8. PubMed PMID: 7560453.