import.msfinder.mssearch: import.MSFinder.mssearch

In sneumann/RAMClustR: RAMClust: a novel feature clustering method enables spectral-matching based annotation for metabolomics data

Description

After running MSFinder on .mat or .msp files, import the spectral search results

Usage

import.msfinder.mssearch(ramclustObj = RC, standardize.names = TRUE,
  mat.dir = NULL, msp.dir = NULL)

Arguments

ramclustObj	R object - the ramclustR object which was used to write the .mat or .msp files
mat.dir	optional path to .mat directory
msp.dor	optional path to .msp directory

Details

this function imports the output from the MSFinder program to annotate the ramclustR object

Value

an updated ramclustR object, with new slots at $msfinder.mssearch.details and $msfinder.mssearch.scores

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.

Tsugawa H, Kind T, Nakabayashi R, Yukihira D, Tanaka W, Cajka T, Saito K, Fiehn O, Arita M. Hydrogen Rearrangement Rules: Computational MS/MS Fragmentation and Structure Elucidation Using MS-FINDER Software. Anal Chem. 2016 Aug 16;88(16):7946-58. doi: 10.1021/acs.analchem.6b00770. Epub 2016 Aug 4. PubMed PMID: 27419259.

sneumann/RAMClustR documentation built on May 30, 2019, 5:05 a.m.