| import.sirius {RAMClustR} | R Documentation |
import.sirius
Description
After running Sirius on .ms files, import the annotation results
Usage
import.sirius(ramclustObj = NULL, ms.dir = NULL, ion.mode = NULL)
Arguments
ramclustObj |
R object - the ramclustR object which was used to write the .mat or .msp files |
ms.dir |
optional path to .mat directory. default = "spectra/ms/out" subdirectory in working directory |
ion.mode |
specify either "N" for negative ionization mode or "P" for positive ionization mode |
Details
this function imports the output from the Sirius program to annotate the ramclustR object
Value
an updated ramclustR object, with new slots at $msfinder.sirius
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.