Package 'metaboData'

Title: Example Metabolomics Data Sets
Description: Data sets from a variety of biological sample matrices, analysed using a number of mass spectrometry based metabolomic analytical techniques. The example data sets are stored remotely using GitHub releases <https://github.com/aberHRML/metaboData/releases> which can be accessed from R using the package. The package also includes the 'abr1' FIE-MS data set from the 'FIEmspro' package <https://users.aber.ac.uk/jhd/> <doi:10.1038/nprot.2007.511>.
Authors: Jasen Finch [aut, cre] , Manfred Beckmann [ctb], David Enot [ctb], Wanchang Lin [ctb]
Maintainer: Jasen Finch <[email protected]>
License: GPL (>= 3)
Version: 0.6.3
Built: 2024-11-01 03:24:28 UTC
Source: https://github.com/aberhrml/metabodata

Help Index


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)

Available data sets

Description

Displays available data sets.

Usage

availableDataSets(dataSetDir = "DataSets", internalDir = TRUE)

Arguments

dataSetDir

directory containing local data set store. If internalDir = TRUE the full directory path would be relative to the package installation location.

internalDir

stored the data set internally to the package installation location

Value

A tibble containing available data set information.

Examples

## Not run: 
availableDataSets()

## End(Not run)

Available files for a data set

Description

Display the available files for a given data set.

Usage

availableFiles(technique, dataSet, dataSetDir = "DataSets", internalDir = TRUE)

Arguments

technique

metabolomic technique name

dataSet

data set name

dataSetDir

directory containing local data set store. If internalDir = TRUE the full directory path would be relative to the package installation location.

internalDir

stored the data set internally to the package installation location

Value

A tibble containing available file information.

Examples

## Not run: 
availableFiles('FIE-HRMS','BdistachyonTechnical')

## End(Not run)

Available data sets for a given technique

Description

Return a vector of available data sets for a given metabolomic technique.

Usage

dataSets(technique)

Arguments

technique

metabolomic technique name

Value

A character vector of available data sets.

Examples

## Not run: 
dataSets(techniques()[1])

## End(Not run)

Data set description

Description

Return list containing experiment description elements

Usage

description(
  technique,
  dataSet,
  dataSetDir = "DataSets",
  internalDir = TRUE,
  ...
)

Arguments

technique

metabolomic technique name

dataSet

data set name

dataSetDir

directory to store local data sets. If internalDir = TRUE this is a directory relative to the library location.

internalDir

Logical, should the directory for storing local data sets be internal to the package location.

...

arguments to pass to downloadDataSet()

Value

A list containing data set descriptors.

Examples

## Not run: 
description(
   techniques()[1],
   dataSets(techniques()[1])[1])

## End(Not run)

Download a data set

Description

Download an example data set.

Usage

downloadDataSet(
  technique,
  dataSet,
  dataSetDir = "DataSets",
  internalDir = TRUE,
  ask = TRUE,
  ...
)

Arguments

technique

metabolomic technique name

dataSet

data set name

dataSetDir

directory to store local data sets. If internalDir = TRUE this is a directory relative to the library location.

internalDir

stored the data set internally to the package installation location

ask

ask before downloading

...

arguments to pass to piggyback::pb_download()

Value

A list object containing the API request response results for the downloaded files.

Examples

## Not run: 
downloadDataSet('FIE-HRMS','BdistachyonTechnical')

## End(Not run)

Download specific files from a data set

Description

Download specific files for a given example data set.

Usage

downloadFiles(
  files,
  technique,
  dataSet,
  dataSetDir = "DataSets",
  internalDir = TRUE,
  ask = TRUE,
  ...
)

Arguments

files

character vector of file paths to download

technique

metabolomic technique name

dataSet

data set name

dataSetDir

directory to store local data sets. If internalDir = TRUE this is a directory relative to the library location.

internalDir

stored the data set internally to the package installation location

ask

ask before downloading

...

arguments to pass to piggyback::pb_download()

Value

A list object containing the API request response results for the downloaded files.

Examples

## Not run: 
downloadFiles(c('31.mzML.gz','32.mzML.gz'),'FIE-HRMS','BdistachyonTechnical')

## End(Not run)

Data set file paths

Description

Return a vector of file paths for a given data set of a given metabolomic technique.

Usage

filePaths(technique, dataSet, dataSetDir = "DataSets", internalDir = TRUE, ...)

Arguments

technique

metabolomic technique name

dataSet

data set name

dataSetDir

directory to store local data sets. If internalDir = TRUE this is a directory relative to the library location.

internalDir

Logical, should the directory for storing local data sets be internal to the package location.

...

arguments to pass to downloadDataSet()

Value

A character vector of file paths.

Examples

## Not run: 
files <- filePaths(
   techniques()[1],
   dataSets(techniques()[1])[1])

head(files)

## End(Not run)

Data set sample information

Description

Return tibble of run information for a given data set of a given metabolomics technique.

Usage

runinfo(technique, dataSet, dataSetDir = "DataSets", internalDir = TRUE, ...)

Arguments

technique

metabolomic technique name

dataSet

data set name

dataSetDir

directory to store local data sets. If internalDir = TRUE this is a directory relative to the library location.

internalDir

Logical, should the directory for storing local data sets be internal to the package location.

...

arguments to pass to downloadDataSet()

Value

A tibble containing sample information.

Examples

## Not run: 
info <- runinfo(
   techniques()[1],
   dataSets(techniques()[1])[1])

head(info)

## End(Not run)

Available data set techniques

Description

Return a vector of available metabolomic techniques.

Usage

techniques()

Value

A character vector of available techniques.

Examples

## Not run: 
techniques()

## End(Not run)