ExposomeSet {rexposome} | R Documentation |
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, ..., 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' 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) ## 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 |
y |
NOT USED |
... |
Argument sent given method. |
object |
An |
method |
Method to be used. |
cmethod |
Function implementing a systsme to retrieve classification from clustering output |
warnings |
If set to |
formula |
Formula, not including exposures, to be tested. |
filter |
Expression to be used to filter |
family |
Family descriving the nature of the health outcome |
tef |
If |
verbose |
If set to |
by.exposure |
If set to |
ngroups |
Number of intervals to be used |
intervals |
If |
select |
Vector selecting thee xposures to be used. |
drop |
If set to |
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 |
messages |
If set to |
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 |
npc |
Number of PC to be kept |
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 |
density |
If set to |
show.trans |
If set to |
x.max |
Threshold for x axis (in %) |
sort |
If set to |
set |
Cantake values |
output |
Can take values |
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.
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