ExposomeSet-class: Class ExposomeSet
In rexposome: Exposome exploration and outcome data analysis

Description Usage Arguments Value Methods (by generic) Slots See Also

Class ExposomeSet contains the exposure levels, the exposure's description and the samples phenotype. It is the starting object for rexposome package and extends eSet.

## S4 method for signature 'ExposomeSet,ANY'
plot(x, y, ...)

## S4 method for signature 'ExposomeSet'
clustering(object, method, cmethod, ..., warnings = TRUE)

## S4 method for signature 'ExposomeSet'
correlation(object, ..., warnings = TRUE)

## S4 method for signature 'ExposomeSet'
dim(x)

## S4 method for signature 'ExposomeSet'
expos(object)

## S4 method for signature 'ExposomeSet'
exposureNames(object)

## S4 method for signature 'ExposomeSet'
exwas(
  object,
  formula,
  filter,
  family,
  ...,
  baselevels,
  tef = TRUE,
  verbose = FALSE,
  warnings = TRUE
)

## S4 method for signature 'ExposomeSet'
familyNames(object, by.exposure = FALSE)

## S4 method for signature 'ExposomeSet'
highAndLow(
  object,
  ngroups = 3,
  intervals = c("standard", "extreme"),
  select,
  drop = FALSE,
  warnings = TRUE
)

## S4 method for signature 'ExposomeSet'
ilod(
  object,
  seed = 1234,
  lod.col = "LOD",
  pNA = 0.2,
  tLog = FALSE,
  method = "QRILC",
  warnings = TRUE,
  ...
)

## S4 method for signature 'ExposomeSet'
imputation(object, select, ..., messages = FALSE)

## S4 method for signature 'ExposomeSet'
invExWAS(object, formula, filter, tef = TRUE, verbose = FALSE, warnings = TRUE)

## S4 method for signature 'ExposomeSet'
mexwas(object, phenotype, family, warnings = TRUE)

## S4 method for signature 'ExposomeSet'
normalityTest(
  object,
  exposure,
  th = 0.05,
  min.val = 5,
  na.rm = TRUE,
  warnings = TRUE
)

## S4 method for signature 'ExposomeSet'
pca(object, npc = 10, pca = FALSE, ...)

## S4 method for signature 'ExposomeSet'
phenotypeNames(object)

## S4 method for signature 'ExposomeSet'
plotFamily(x, family, group, group2, scatter = TRUE, na.omit = TRUE)

## S4 method for signature 'ExposomeSet'
plotHistogram(x, select, density = TRUE, show.trans = FALSE)

## S4 method for signature 'ExposomeSet'
plotLOD(object, lod.col = "LOD", x.max = 100, sort = TRUE)

## S4 method for signature 'ExposomeSet'
plotMissings(
  object,
  set = c("exposures", "phenotypes"),
  x.max = 100,
  sort = TRUE
)

## S4 method for signature 'ExposomeSet'
standardize(object, select, method = "normal", na.rm = TRUE, warnings = TRUE)

## S4 method for signature 'ExposomeSet'
Summary(x, set = c("exposures", "phenotypes"), select, ..., na.rm = FALSE)

## S4 method for signature 'ExposomeSet'
tableLOD(object, output = "n", lod.col = "LOD", sort = TRUE)

## S4 method for signature 'ExposomeSet'
tableMissings(
  object,
  set = c("exposures", "phenotypes"),
  output = "n",
  sort = TRUE
)

## S4 method for signature 'ExposomeSet'
trans(object, fun, select, by.exposure = FALSE, ...)

`x`	An `ExposomeSet` object.
`y`	NOT USED
`...`	Arguments to be passed to imputeFAMD
`object`	An `ExposomeSet` object.
`method`	Method to be used.
`cmethod`	Function implementing a systsme to retrieve classification from clustering output
`warnings`	If set to `TRUE` it prints the warning messsages.
`formula`	Formula, not including exposures, to be tested. No need to provide response (left term)
`filter`	Expression to be used to filter `ExposomeSet`
`family`	Family descriving the nature of the health outcome
`baselevels`	Labeled vector with the default base level for categorical exposures.
`tef`	If `TRUE` it computed the threshold for effective tests.
`verbose`	If set to `TRUE` is shows messages on progression.
`by.exposure`	If set to `TRUE` ir returns the family which each exposure belongs
`ngroups`	Number of intervals to be used
`intervals`	If `"standard"` all levels are kept, if `"extreme"` intermetiate levels are set to `NA`.
`select`	Vector selecting thee xposures to be used.
`drop`	If set to `TRUE` exposures are replaced
`seed`	Numeric seed
`lod.col`	Indicator of the column where the LOD is located
`pNA`	Maximum percentage allowed of values under LOD
`tLog`	If set to `TRUE` it transforms all the exposures to lod before the imputation.
`messages`	If set to `TRUE` messages from `mice`'s function will be displayed.
`phenotype`	Health outcome to be used as dependent variable.
`exposure`	Vecror of exposures to be used.
`th`	Threshold of P-Value used to considere normalit
`min.val`	Minimum number of observations to perform test
`na.rm`	If set to `TRUE` removes `NA` values
`npc`	Number of PC to be kept
`pca`	Perform PCA (only numerical variables) or FAMD (numerical and categorical)
`group`	Phenotype to group exposures
`group2`	Phenotype to group exposures
`scatter`	If set to true it shows the samples value in the plot
`na.omit`	If set to `TRUE`, `NA` values are discarded
`density`	If set to `TRUE` a desntiry plot is draw on the histogram
`show.trans`	If set to `TRUE`, three extra plots are drawn with usual transformations
`x.max`	Threshold for x axis (in %)
`sort`	If set to `TRUE`, results are ordered
`set`	Cantake values `"exposures"` or `"phentoypes"`.
`output`	Can take values `"n"` (count) ot `"p"` (percentage)
`fun`	Function to bt used in the transformation process

An object of class ExposomeSet

plot: Wrapper for plotFamily method.
clustering: Performs clustering on samples based on exposure levels.
correlation: Computes correlation on exposures.
dim: Returns the number of exsures, samples and phenotypes.
expos: Returns a data.frame with exposures.
exposureNames: Getter to obtain the exposures's names.
exwas: Performs an EXposome-Wide Association Study
familyNames: Getter to obtain the families's names of the family of each exposure.
highAndLow: Performs a discretization of continuous exposures.
ilod: Imputation of under-LOD values of exposures.
imputation: Imputation of missing values of exposures.
invExWAS: Performs an EXposome-Wide Association Study (modelling the exposures as response)
mexwas: Performs a Multiple-EXposure-Wide Association Study.
normalityTest: Test the normality of each exposure.
pca: Performs a PCA
phenotypeNames: Getter to obtain the phenotypes's names.
plotFamily: Draws a boxplot or accumulated-bar plot for each exposure in a given family.
plotHistogram: Draws an histogram of a given continuous exposure or a pie chart if a given categorycal exposure.
plotLOD: Draws a barchart with the amount of under-LOD values.
plotMissings: Draws a bar-plot with the amount of missing values.
standardize: Standardization of exposures.
Summary: Summary of both continuous and categorical exposures
tableLOD: Returns a vector with the number of under-LOD values per exposure.
tableMissings: Returns a vector with the number of missing values per exposure.
trans: Transformation of exposures.

assayData: Contains the exposures matrix with column number equal to nrow(phenoData) (see eSet, AssayData).
featureData: Contains the description of the exposures including the family where they belong (see eSet, AnnotatedDataFrame).
phenoData: Contains the phenotypes or variables experimenter-supplied (see eSet, AnnotatedDataFrame).

readExposome to create an ExposomeSet from files, loadExposome to create an ExposomeSet from data.frames