cls: Sample meta information wrangling

In jasenfinch/metabolyseR: Methods for Pre-Treatment, Data Mining and Correlation Analyses of Metabolomics Data

Sample meta information wrangling

Description

Query or alter sample meta information in AnalysisData or Analysis class objects.

Replace a given sample info column from an Analysis or AnalysisData object.

Usage

clsAdd(d, cls, value, ...)

## S4 method for signature 'AnalysisData'
clsAdd(d, cls, value)

## S4 method for signature 'Analysis'
clsAdd(d, cls, value, type = c("pre-treated", "raw"))

clsArrange(d, cls = "class", descending = FALSE, ...)

## S4 method for signature 'AnalysisData'
clsArrange(d, cls = "class", descending = FALSE)

## S4 method for signature 'Analysis'
clsArrange(
  d,
  cls = "class",
  descending = FALSE,
  type = c("pre-treated", "raw")
)

clsAvailable(d, ...)

## S4 method for signature 'AnalysisData'
clsAvailable(d)

## S4 method for signature 'Analysis'
clsAvailable(d, type = c("pre-treated", "raw"))

clsExtract(d, cls = "class", ...)

## S4 method for signature 'AnalysisData'
clsExtract(d, cls = "class")

## S4 method for signature 'Analysis'
clsExtract(d, cls = "class", type = c("pre-treated", "raw"))

clsRemove(d, cls, ...)

## S4 method for signature 'AnalysisData'
clsRemove(d, cls)

## S4 method for signature 'Analysis'
clsRemove(d, cls, type = c("pre-treated", "raw"))

clsRename(d, cls, newName, ...)

## S4 method for signature 'AnalysisData'
clsRename(d, cls, newName)

## S4 method for signature 'Analysis'
clsRename(d, cls, newName, type = c("pre-treated", "raw"))

clsReplace(d, value, cls = "class", ...)

## S4 method for signature 'AnalysisData'
clsReplace(d, value, cls = "class")

## S4 method for signature 'Analysis'
clsReplace(d, value, cls = "class", type = c("pre-treated", "raw"))

Arguments

d	S4 object of class Analysis or AnalysisData
cls	sample info column to extract
value	vactor of new sample information for replacement
...	arguments to pass to specific method
type	raw or pre-treated sample information
descending	TRUE/FALSE, arrange samples in descending order
newName	new column name

Methods

• clsAdd: Add a sample information column.

• clsArrange: Arrange sample row order by a specified sample information column.

• clsAvailable: Retrieve the names of the available sample information columns.

• clsExtract: Extract the values of a specified sample information column.

• clsRemove: Remove a sample information column.

• clsRename: Rename a sample information column.

• clsReplace: Replace a sample information column.

Examples

library(metaboData)
d <- analysisData(abr1$neg,abr1$fact)

## Add a sample information column named 'new'
d <- clsAdd(d,'new',1:nSamples(d))

print(d)

## Arrange the row orders by the 'day' column
d <- clsArrange(d,'day')

clsExtract(d,'day')

## Retreive the available sample information column names
clsAvailable(d)

## Extract the values of the 'day' column
clsExtract(d,'day')

## Remove the 'class' column
d <- clsRemove(d,'class')

clsAvailable(d)

## Rename the 'day' column to 'treatment'
d <- clsRename(d,'day','treatment')

clsAvailable(d)

## Replace the values of the 'treatment' column
d <- clsReplace(d,rep(1,nSamples(d)),'treatment')

clsExtract(d,'treatment')

jasenfinch/metabolyseR documentation built on Sept. 18, 2023, 1:25 a.m.