abr1: The abr1 dataset

In metaboData: Example Metabolomics Data Sets

The abr1 dataset

Description

Real world FIE-MS dataset.

Usage

data(abr1)

Details

FIE-MS data matrices developed from analysis of samples representing a time course of pathogen attack in a model plant species (Brachypodium distachyon). The data was developed in a single batch with all samples randomised using a Thermo LTQ linear ion trap processed using fiems_ltq_main. Both positive and negative ion mode are given (abr1$pos and abr1$neg). To avoid confusions, variable names are given with a letter corresponding to the ionisation mode followed by the actual nominal mass value (e.g. P130 corresponds to the nominal mass 130 in the positive mode).

Experimental factors are given in the abr1$fact data frame:

• injorder: sample injection order

• name: sample name

• rep: biological replicate for a given class

• day: number of days following infection after which the sample has been harvested - Level H corresponds to an healthy plant.

• class: identical to day except that class=6 when day=H

• pathcdf,filecdf,name.org,remark: are generated from profile processing and are kept for traceability purposes.

Factor of interest for classification are contained in abr1$fact$day. There are 20 biological replicates in each class has

Value

A list with the following elements:

fact	A data frame containing experimental meta-data.
pos	A data frame for positive data with 120 observations and 2000 variables.
neg	A data frame for negative data with 120 observations and 2000 variables.

Author(s)

Manfred Beckmann, David Enot and Wanchang Lin

Source

The FIEmspro package https://github.com/aberHRML/FIEmspro

Examples

# Load data set
data(abr1)

# Select data set
dat <- abr1$neg

# number of observations and variables in the negative mode matrix
dim(dat)

# names of the variables
dimnames(dat)[[2]] %>% 
 head()

# print out the experimental factors
abr1$fact %>% 
 head()

# check out the repartition of class
table(abr1$fact$class)

metaboData documentation built on March 18, 2022, 5:19 p.m.