Description Usage Arguments Value Author(s) See Also Examples
View source: R/metaboliteTable.R
Takes a MAIT-class
object and builds a table with the information related to the significant features and their possible identifications.
1 2 | metaboliteTable(MAIT.object,
printCSVfile = FALSE)
|
MAIT.object |
A MAIT-class object where significant features have already been found. |
printCSVfile |
A boolean parameter. Set to TRUE if a csv file should be written with the metabolite table. |
An output table is stored in the folder (working directory)/Tables/SearchTable.csv having the fields:
First column: search ID number.
Second column (mz): Peak mass.
Third column(rt): Peak retention time (in minutes).
The columns from the third to the column labeled "p.adj" contain number of class samples where the peak has been detected and the intensities of the peak among samples.
The P.adjust column contains the corrected peak p-value using bonferroni.
The p column shows the peak p-value with no multiple test correction.
The Fisher column shows the FIsher test results for the peak. Each of the letters separated by the character "_" corresponds to a class value. Classes having the same letters are indistinguible whereas those having different letters are statistically different clases.
The isotopes column shows if the peak has been identified as a possible isotope.
The adduct column shows which kind of adduct or biotransformation could the peak be.
Column Name contains the name of the possible metabolite identification for the peak.
The column labeled spectra contains the spectral ID of the peak.
Column Biofluid shows if the identified search is stored as a biofluid in the input database or not.
The column ENTRY shows the database name of the entry for the metabolite.
Francesc Fernandez, francesc.fernandez.albert@upc.edu
identifyMetabolites
spectralAnova
spectralTStudent
1 2 3 4 5 | data(MAIT_sample)
MAIT<-spectralSigFeatures(MAIT,p.adj="fdr",parametric=TRUE)
MAIT<-Biotransformations(MAIT.object = MAIT, peakPrecision = 0.005)
MAIT <- identifyMetabolites(MAIT.object = MAIT, peakTolerance = 0.005,polarity="positive")
head(metaboliteTable(MAIT))
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