Package 'omicRexposome'

Title: Exposome and omic data associatin and integration analysis
Description: omicRexposome systematizes the association evaluation between exposures and omic data, taking advantage of MultiDataSet for coordinated data management, rexposome for exposome data definition and limma for association testing. Also to perform data integration mixing exposome and omic data using multi co-inherent analysis (omicade4) and multi-canonical correlation analysis (PMA).
Authors: Carles Hernandez-Ferrer [aut, cre], Juan R. González [aut]
Maintainer: Xavier Escribà Montagut <[email protected]>
License: MIT + file LICENSE
Version: 1.27.0
Built: 2024-06-30 06:36:34 UTC
Source: https://github.com/bioc/omicRexposome

Help Index

Method to add an ExposomeClust to a MultiDataSet

Description

This method allows to insert an object of class ExposomeClust as an independent dataset into an object of class MultiDataSet.

Usage

add_cls(object, clsSet, ...)

## S4 method for signature 'MultiDataSet,ExposomeClust'
add_cls(object, clsSet, ...)

Arguments

object

An object of class MultiDataSet.
clsSet

An object of class ExposomeClust.
...

Arguments given to add_eset from MultiDataSet.

Value

A MultiDataSet with the ExpressionSet added as an independent dataset.

Examples

data("eclust", package = "rexposome")
library(MultiDataSet)
md <- new("MultiDataSet")
names(md)
md <- add_cls(md, expo_c)
names(md)

Method to add an ExposomeSet to a MultiDataSet

Description

This method allows to insert an object of class ExposomeSet as an independent dataset into an object of class MultiDataSet.

Usage

add_exp(object, expoSet, warnings = TRUE, ...)

## S4 method for signature 'MultiDataSet,ExposomeSet'
add_exp(object, expoSet, warnings = TRUE,
  ...)

Arguments

object

An object of class MultiDataSet.
expoSet

An object of class ExposomeSet.
warnings

(default TRUE) If set to FALSE warnings will not be displayed.
...

Arguments given to add_eset from MultiDataSet.

Value

A MultiDataSet with the ExpressionSet added as an independent dataset.

Examples

data("exposome", package = "rexposome")
library(MultiDataSet)
md <- new("MultiDataSet")
names(md)
md <- add_exp(md, expo)
names(md)

ResultSet for testing and illustration purpouses

Description

ResultSet created using association method, testing proteome association to exposome ("mds"), adjusted by sex and age.

Usage

data("asr")

Format

An object of class ResultSet of length 15.

Value

A ResultSet object.

Examples

data("asr", package = "omicRexposome")
asr

# —————————————————————————– Method to perform an association study between transcriptome and exposom

Description

This function allows to perform an association study between gene expression from microarray and the exposome. An ExpresionSet is the object storing the gene expresion and an ExposomeSet the one storing the exposome. Both of them needs to be encapsulated in a MultiDataSet. The association study is perform through standard limma pipeline. The function allows to perform multiple tests using the argument exposures.

Usage

association(object, formula, expset, omicset, set = "exposures",
  method = "ls", ..., baselevels, sva = "none", vfilter = NULL,
  verbose = FALSE, warnings = TRUE)

## S4 method for signature 'MultiDataSet'
association(object, formula, expset, omicset,
  set = "exposures", method = "ls", ..., baselevels, sva = "none",
  vfilter = NULL, verbose = FALSE, warnings = TRUE)

Arguments

object

A MultiDataSet object containing at last one omic data-sets like ExpressionSet, MethylationSet... and, at last, one ExposomeSet.
formula

formula to be evaluated by each exposure (or phenotype, see set argument). It should not contain any exposures (or phenotype), it will be added automatically when evaluated.
expset

Name of the ExposomeSet in object.
omicset

Name of the omic data-set in object.
set

(default "exposures") Can take value "exposures" to test the association of the exposures in the ExposomeSet vs. the features in the omic data-set. If takes "phenotypes" all phenotypes in ExposomeSet are tested.
method

(default "lm") Check limma help pages.
...

Arguments passed to limma's lmFit.
baselevels

(optional) If set, must be a labeled vector with the default base level for categorical exposures.
sva

(default "none"). This argument can take value "none" to do not apply SVA. Value "fast" will run SVA using isva and SmartSVA. Value "slow" will run SVA using sva.
vfilter

(default NULL). Only used when sva = "slow". Numeric number of probes used in sva. Recomended ~10% of real probes.
verbose

(default FALSE) If set to TRUE, a series of messages descriving the process are shown.
warnings

(default TRUE) If set to TRUE, a series of warnings are shown when required user atention.

Value

An object of class ResultSet.

Examples

library(MultiDataSet)
data(brge_prot, package = "brgedata")
data(brge_expo, package = "brgedata")
mds <- createMultiDataSet()
mds <- add_eset(mds, brge_prot, dataset.type = "proteines")
mds <- add_eset(mds, brge_expo, dataset.type = "exposures", GRanges = NA)

asr <- association(mds, formula = Asthma ~ Sex + Age,
  expset = "exposures", omicset = "proteines")
asr

Function to perform a Transcriptome-Wide Association Study

Description

This function allows to perform a Transcriptome-Wide Association Study by using an ExposmeSet and an ExpressionSet. It allows to perform an adjustment using Surrogate Variable Analysis (from R package sva).

Usage

crossomics(object, method = "mcca", ncomponents = 2, ..., na.rm = FALSE,
  permute = c(100, 3), verbose = FALSE, warnings = TRUE)

## S4 method for signature 'MultiDataSet'
crossomics(object, method = "mcca",
  ncomponents = 2, ..., na.rm = FALSE, permute = c(100, 3),
  verbose = FALSE, warnings = TRUE)

Arguments

object

A MultiDataSet object containing at last two data-sets like ExposomeSet, ExpressionSet, MethylationSet...
method

(default "mcca") It can takes values "mcca" for Multiple Canonical Correlation Analysis or "mcia" for Multiple Co-Inertia Analysis.
ncomponents

(default 2) Number of components to be estimated.
...

Other arguments given to mcia (from omicade4) or to MultiCCA (from PMA).
na.rm

(default FALSE) If method was set to "mcca" and na.rm was set to TRUE, features containing missing values are removed.
permute

(default c(100, 3)). If method="mcca" and this agument is set to NULL no permutation test to tune-up the parameters for MultiCCA. When filles, permute[1] corresponds to the number permutations (default in MultiCCa.permute is 25) and permute[2] the number of iterations (default in MultiCCA.permute is 3).
verbose

(default FALSE) If set to TRUE, a series of messages descriving the process are shown.
warnings

(default TRUE) If set to TRUE, a series of warnings are shown when required user atention.

Value

An object of class ResultSet.

Examples

library(MultiDataSet)
library(rexposome)
data(brge_prot, package = "brgedata")
data(brge_expo, package = "brgedata")
mds <- createMultiDataSet()
mds <- add_eset(mds, brge_prot, dataset.type = "proteines")
mds <- add_eset(mds, imputation(brge_expo),
    dataset.type = "exposures", GRanges = NA)

crs <- crossomics(mds, method = "mcia")
crs

ResultSet for testing and illustration purpouses

Description

ResultSet created using crossomics method, selecting "mcia" method. Result from the integration of proteome and exposome data ("mds").

Usage

data("crs")

Format

An object of class ResultSet of length 1.

Value

A ResultSet object.

Examples

data("crs", package = "omicRexposome")
crs

Method to extrat integration-feature result from a ResultSet

Description

Homologous methods from MultiDataSet (getAssociation) but for ResultsSet created by crossomics. It Resturns a data.frame with the result from mcia (omicade4) or from MultiCCA (PMA).

Usage

getIntegration(object, ...)

## S4 method for signature 'ResultSet'
getIntegration(object, ...)

Arguments

object

An object of class ResultSet obtained from
...

NOT USED

Value

A data.frame

Examples

data("crs", package = "omicRexposome")
class(getIntegration(crs))

MultiDataSet for testing and illustration purpouses

Description

MultiDataSet containing both proteome data-set and exposome data-set.

Usage

data("mds")

Format

An object of class MultiDataSet of length 2.

Value

A MultiDataSet object.

Examples

data("mds", package = "omicRexposome")
mds

omicRexposome: Package for exposome and omic data associatin and integration

Description

omicRexposome: Package for exposome and omic data associatin and integration

exposome-omic data association study

The packages offers the function association that allows to perform an association study using transcriptome, methylome, etc. as dependent variable and exposome data as independent variable. The function relies on limma pipeline and generates an object of class ResultSet, that can be ploted using plotAssociation.

exposome-omic data integration study

The packages offers the function crossomics that allows to perform two types of integration study: Multi Canonical Correlation Analysis and Multi Co-Inertia Analysis. The function allos to use any type and number of datasets (aka. exposome transcriptome, methylome, etc.). The function generates an object of class ResultSet, that can be ploted using plotIntegration.

Function to draw de result of an association study

Description

This function draws two type of plots for the ResultSet from association functions

Usage

plotAssociation(object, rid = 1, coef = 2, contrast = 1,
  type = c("manhattan", "qq", "volcano"), tPV = NULL, tFC = NULL,
  show.effect = FALSE)

## S4 method for signature 'ResultSet'
plotAssociation(object, rid = 1, coef = 2,
  contrast = NULL, type = c("manhattan", "qq", "volcano"), tPV = NULL,
  tFC = NULL, show.effect = FALSE)

Arguments

object

An object of class ResultSet obtained from assoc_* functions.
rid

(default 1) Index or name of the test to be plotted.
coef

(default 2) Index of the coefficient to be extracted.
contrast

(default 1) When code corresponds to a multicategorical variable, contasr selects the comparison.
type

Can take "volcano", "qq", "manhattan" and "protein". "protein" lot is a type of Manhattan plot designed for protein association analysis.
tPV

(optional) Threshold for P.Value when type="volcano".
tFC

(optional) Threshold for Fold Change or Effect when type="volcano".
show.effect

(default FALSE) If set to TRUE, when type="volcano" the X-axis will show 2^logFC instead of logFC.

Value

A ggplot2 object

See Also

plotIntegration for plotting integration results. association to create a ResultSet to be passed to this function.

Examples

data("asr", package = "omicRexposome")
plotAssociation(asr, type = "qq")
plotAssociation(asr, type = "volcano")

Plot number of hits per result in ResultSet

Description

This method draws a barplot with the number of hits in each result stored in the given ResultSet.

Usage

plotHits(object, th = 0.05, width = 0.75)

## S4 method for signature 'ResultSet'
plotHits(object, th = 0.05, width = 0.75)

Arguments

object

An object of class ResultSet
th

(default 0.05) Threshold (p-value) to considere a result as a hit.
width

(default 0.70) width of the bar

Value

A ggplot2 object

See Also

plotLambda for a graphical representation of the lambda score per analysys, tableLambda for the lambda score per analysys, tableHits for the hists per analysys

Examples

data(asr, package = "omicRexposome")
plotHits(asr)

Function to draw de result of an integration study

Description

This function draws a plots for the ResultSet from integration function

Usage

plotIntegration(object, cmpX = 1, cmpY = 2, lb.th = 0.2,
  legend.show = TRUE, colors, ...)

## S4 method for signature 'ResultSet'
plotIntegration(object, cmpX = 1, cmpY = 2,
  lb.th = 0.2, legend.show = TRUE, colors, ...)

Arguments

object

An object of class ResultSet obtained from crossomics.
cmpX

(default 1) Value of the X-axis when ploting rsults from mcia.
cmpY

(default 2) Value of the Y-axis when ploting rsults from mcia.
lb.th

(default 0.20) Threshold to place labels on radar chart drawn when ploting results from MultiCCA.
legend.show

(default TRUE) If set to FALSE, right legend of radar plot is hidden when ploting results from MultiCCA.
colors

(optional) Names vector with the colors sued to draw each dataset. Used when ploting results from MultiCCA. If missing, random colores are chosen.
...

Optional arguments are given to plot from omicade4 pacage (argument axes is filled with values from cmpX and cmpY).

Value

A ggplot2 object

See Also

plotAssociation for plotting association results. crossomics to create a ResultSet to be passed to this function.

Examples

data("crs", package = "omicRexposome")
plotIntegration(crs)

Plot lambda score for all results in a ResultSet

Description

This method draws a baplor with the lambda score of each result in the given ResultSet.

Usage

plotLambda(object, width = 0.75)

## S4 method for signature 'ResultSet'
plotLambda(object, width = 0.75)

Arguments

object

An object of class ResultSet
width

(default 0.70) width of the bar

Value

A ggplot2 object

See Also

plotHits for a graphical representation of the hits per analysys, tableLambda for the lambda score per analysys, tableHits for the hists per analysys

Examples

data("asr", package = "omicRexposome")
plotLambda(asr)

Transforms the discrete genotype from a snpSet to a matrix of a continuous variable.

Description

The function converts the categorical variable of SNPs to a continuous variable by normalizing each SNP as described in Abraham G. and Inouye M. 2014 (DOI: 10.1371/journal.pone.0093766).

Usage

snpToContinuous(snpSet, verbose = FALSE)

Arguments

snpSet

An object of class snpSet with set calls slot .
verbose

If set to TRUE, messages will be shown.

Value

An matrix of the calls of the SNPs converted to a continuous variable.

See Also

crossomics use this function

Counts the number of hits on the results stored in a ResultSet

Description

Given a threshold it counts the number of hits in each result in the given ResultSet.

Usage

tableHits(object, th = 0.05)

## S4 method for signature 'ResultSet'
tableHits(object, th = 0.05)

Arguments

object

An object of class ResultSet
th

(default 0.05) Threshold (p-value) to considere a result as a hit.

Value

A labeled numeric vector with the exposures and the number of hits.

See Also

tableLambda for the lambda score per analysys, plotLambda for a graphical representation of the lambda score per analysys, plotHits for a graphical representation of the hists per analysys

Examples

data("asr", package = "omicRexposome")
tableHits(asr)

Compute a lambda score on the results stored in a ResultSet

Description

Compute lambda score on each result in the given ResultSet by using lambdaClayton.

Usage

tableLambda(object, trim = 0.5)

## S4 method for signature 'ResultSet'
tableLambda(object, trim = 0.5)

Arguments

object

An object of class ResultSet
trim

(default 0.5) percentage of right omited values for lambdaClayton.

Value

Returns a data.frame having the exposures and the computed lambda score.

A labeled numeric vector with the lambda score for each exposure.

See Also

tableHits for the number of hits per analysys, plotHits for a graphical representation of the hists per analysys, plotLambda for a graphical representation of the lambda score per analysys

Examples

data("asr", package = "omicRexposome")
tableLambda(asr)