R/MBR-methods.R
In chagasVinicius/RTNmotifs: analysis of co-regulatory network motifs and inference of 'dual regulons'.
################################################################################
########################## MBR-methods ############################
################################################################################
##------------------------------------------------------------------------------
#########################################
###class builder
#########################################
.MBRmaker <-
function(class="MBR", gexp=gexp,
regulatoryElements1=regulatoryElements1,
regulatoryElements2=regulatoryElements2)
{
#---creates the 'MBR' object
object <- newMBR(class=class, gexp=gexp,
regulatoryElements1=regulatoryElements1,
regulatoryElements2=regulatoryElements2,
TNI1=NULL, TNI2=NULL,
testedElementsTNI1=character(),
testedElementsTNI2=character(),
dualRegulons=character(),
results=list(), para=list(), summary=list(),
status=character())
#---status
status <- rep('[ ]', 1, 5)
names(status) <- c('Preprocess', 'Permutation',
'Bootstrap', 'DPI.filter',
'Association')
#---parameters
sum.info.para <- list()
sum.info.para$TNIs$perm <- NA
sum.info.para$TNIs$boot <- NA
sum.info.para$TNIs$dpi <- NA
sum.info.para$MBR$association <- matrix(NA, 1, 3)
colnames(sum.info.para$MBR$association) <- c('minRegulonSize',
'prob',
'estimator')
rownames(sum.info.para$MBR$association) <- 'Parameter'
#---summary motifsInformation
sum.info.summary <- list()
sum.info.summary$MBR$Duals <- matrix(NA, 1, 1)
colnames(sum.info.summary$MBR$Duals) <- 'numberDuals'
rownames(sum.info.summary$MBR$Duals) <- 'duals'
#---set
object <- .mbr.set(name="status", para=status, object=object)
object <- .mbr.set(name="para", para=sum.info.para, object=object)
object <- .mbr.set(name="summary", para=sum.info.summary, object=object)
return(object)
}
#----------------------------------------------------------
#it creates the 'MBR' class object
newMBR <-
function(class, gexp, regulatoryElements1, regulatoryElements2,
TNI1, TNI2, testedElementsTNI1, testedElementsTNI2,
dualRegulons, results, para, summary, status)
{
#---checks
if(missing(gexp)) stop("NOTE: 'gexp' is missing ", call.=FALSE)
if(missing(regulatoryElements1))
stop("NOTE: 'regulatoryElements1' is missing", call.=FALSE)
if(missing(regulatoryElements2))
stop("NOTE: 'regulatoryElements2' is missing", call.=FALSE)
mbr.checks(name='TNI', TNI1)
mbr.checks(name='TNI', TNI2)
mbr.checks(name='testedElementsTNI', testedElementsTNI1)
mbr.checks(name='testedElementsTNI', testedElementsTNI2)
mbr.checks(name='dualRegulons', dualRegulons)
mbr.checks(name='results', results)
mbr.checks(name='para', para)
mbr.checks(name='summary', summary)
mbr.checks(name='status', status)
mbr.checks(name='gexp', gexp)
mbr.checks(name='regulatoryElements1', regulatoryElements1)
mbr.checks(name='regulatoryElements2', regulatoryElements2)
#---creating TNIs
regulonsTNI1 <- new("TNI", gexp=gexp,
transcriptionFactors=regulatoryElements1)
regulonsTNI2 <- new("TNI", gexp=gexp,
transcriptionFactors=regulatoryElements2)
#---creating the MBR-object
new(class, TNI1=regulonsTNI1, TNI2=regulonsTNI2,
testedElementsTNI1=testedElementsTNI1,
testedElementsTNI2=testedElementsTNI2,
dualRegulons=dualRegulons, results=results,
para=para, summary=summary, status=status)
}
##------------------------------------------------------------------------------
#' A preprocessing function for objects of class MBR.
#'
#' @param gexp A numerical matrix, typically with mRNA and/or miRNA expression
#' values.
#' @param regulatoryElements1 A named vector with regulatory elements listed in
#' 'gexp' rownames.
#' @param regulatoryElements2 A named vector with regulatory elements listed in
#' 'gexp' rownames.
#' @param verbose A single logical value specifying to display detailed
#' messages (when verbose=TRUE) or not (when verbose=FALSE).
#' @param ... Additional arguments passed on to
#' \code{\link[RTN:tni.preprocess]{tni.preprocess}} function.
#' @return A preprocessed 'MBR-class' object.
#' @examples
#' data("dt4rtn", package = "RTN")
#' gexp <- dt4rtn$gexp
#' annot <- dt4rtn$gexpIDs
#' tfs1 <- dt4rtn$tfs[c("IRF8","IRF1","PRDM1","AFF3","E2F3")]
#' tfs2 <- dt4rtn$tfs[c("HCLS1","STAT4","STAT1","LMO4","ZNF552")]
#' ##---mbrPreprocess
#' rmbr <- mbrPreprocess(gexp=gexp, regulatoryElements1 = tfs1,
#' regulatoryElements2=tfs2, gexpIDs=annot)
#'
#' @import RTN
#'
#' @import methods
#' @docType methods
#' @rdname mbrPreprocess-methods
#' @aliases mbrPreprocess
#' @export
##Regulons pre-processing method
setMethod("mbrPreprocess",
"matrix",
function(gexp, regulatoryElements1, regulatoryElements2,
verbose=TRUE,...)
{
##---
mbr.checks(name="verbose", para=verbose)
object <- .MBRmaker(class="MBR", gexp=gexp,
regulatoryElements1=regulatoryElements1,
regulatoryElements2=regulatoryElements2)
##---get TNIs
TNI1 <- mbrGet(object, what="TNI1")
TNI2 <- mbrGet(object, what="TNI2")
##---pre-processing TNIs
if(verbose) cat("-Preprocessing TNI objects...\n\n")
TNI1 <- tni.preprocess(TNI1, verbose=verbose,...=...)
TNI2 <- tni.preprocess(TNI2, verbose=verbose,...=...)
tfs1 <- tni.get(TNI1, what="tfs")
tfs2 <- tni.get(TNI2, what="tfs")
mbr.checks(name="regulatoryElements",
para=c(tfs1,tfs2))
##---set
object <- .mbr.set(name="TNI1", para=TNI1, object=object)
object <- .mbr.set(name="TNI2", para=TNI2, object=object)
object <- .mbr.set(name="statusUpdate",
para="Preprocess", object=object)
return(object)
}
)
##------------------------------------------------------------------------------
#' Inference of transcriptional networks.
#'
#' This function takes an MBR object and computes two transcriptional networks
#' inferred
#' by mutual information (with multiple hypothesis testing corrections).
#'
#' @param object A preprocessed object of class \linkS4class{MBR}.
#' @param verbose A single logical value specifying to display detailed
#' messages (when verbose=TRUE) or not (when verbose=FALSE).
#' @param ... Additional arguments passed on to the
#' \code{\link[RTN:tni.permutation]{tni.permutation}} function.
#' @return An \linkS4class{MBR} object with two mutual information matrices,
#' one in each "TNI" slot.
#' @examples
#' data("dt4rtn", package = "RTN")
#' gexp <- dt4rtn$gexp
#' annot <- dt4rtn$gexpIDs
#' tfs1 <- dt4rtn$tfs[c("IRF8","IRF1","PRDM1","AFF3","E2F3")]
#' tfs2 <- dt4rtn$tfs[c("HCLS1","STAT4","STAT1","LMO4","ZNF552")]
#' ##---mbrPreprocess
#' rmbr <- mbrPreprocess(gexp=gexp, regulatoryElements1 = tfs1,
#' regulatoryElements2=tfs2, gexpIDs=annot)
#' ##---mbrPermutation
#' rmbr <- mbrPermutation(rmbr, nPermutations=10)
#'
#' @import RTN
#'
#' @import methods
#' @docType methods
#' @rdname mbrPermutation-methods
#' @aliases mbrPermutation
#' @export
## permutation
setMethod("mbrPermutation",
"MBR",
function(object, verbose=TRUE, ...)
{
##---checks
mbr.checks(name="object", para=object)
mbr.checks(name="verbose", para=verbose)
##---get TNIs
TNI1 <- mbrGet(object, what="TNI1")
TNI2 <- mbrGet(object, what="TNI2")
##---permutation TNIs
if(verbose)
cat("-Performing permutation analysis for two TNI objects...\n\n")
TNI1 <- tni.permutation(TNI1, verbose=verbose,...=...)
TNI2 <- tni.permutation(TNI2, verbose=verbose,...=...)
#---get
tni1_summary <- tni.get(TNI1, what="summary")
tni2_summary <- tni.get(TNI2, what="summary")
mbr_summary <- mbrGet(object, what="summary")
mbr_para <- mbrGet(object, what="para")
#---changes
mbr_para$TNIs$perm <- tni1_summary$para$perm
mbr_summary$TNIs$TNI1 <- tni1_summary$results$tnet
colnames(mbr_summary$TNIs$TNI1) <- c('RE', 'Targets', 'Edges')
mbr_summary$TNIs$TNI2 <- tni2_summary$results$tnet
colnames(mbr_summary$TNIs$TNI2) <- c('RE', 'Targets', 'Edges')
#---set
object <- .mbr.set(name="TNI1", para=TNI1, object=object)
object <- .mbr.set(name="TNI2", para=TNI2, object=object)
object <- .mbr.set(name="statusUpdate",
para="Permutation", object=object)
object <- .mbr.set(name="para", para=mbr_para, object=object)
object <- .mbr.set(name="summary", para=mbr_summary, object=object)
return(object)
}
)
#' Inference of consensus transcriptional networks.
#'
#' This function takes an MBR object and computes two consensus transcriptional
#' networks.
#'
#' @param object A processed objec of class \linkS4class{MBR} evaluated by the
#' method \code{\link[RTNduals:mbrPermutation]{mbrPermutation}}.
#' @param verbose A single logical value specifying to display detailed
#' messages (when verbose=TRUE) or not (when verbose=FALSE).
#' @param ... Additional arguments passed to the
#' \code{\link[RTN:tni.bootstrap]{tni.bootstrap}} function.
#' @return An \linkS4class{MBR} object with two consensus mutual information
#' matrices, one in each "TNI" slot.
#' @examples
#' data("dt4rtn", package = "RTN")
#' gexp <- dt4rtn$gexp
#' annot <- dt4rtn$gexpIDs
#' tfs1 <- dt4rtn$tfs[c("IRF8","IRF1","PRDM1","AFF3","E2F3")]
#' tfs2 <- dt4rtn$tfs[c("HCLS1","STAT4","STAT1","LMO4","ZNF552")]
#' ##---mbrPreprocess
#' rmbr <- mbrPreprocess(gexp=gexp, regulatoryElements1 = tfs1,
#' regulatoryElements2=tfs2, gexpIDs=annot)
#' ##---mbrPermutation
#' rmbr <- mbrPermutation(rmbr, nPermutations=10)
#' ##---mbrBootstrap
#' rmbr <- mbrBootstrap(rmbr, nBootstrap=10)
#'
#' @import RTN
#'
#' @import methods
#' @docType methods
#' @rdname mbrBootstrap-methods
#' @aliases mbrBootstrap
#' @export
##------------------------------------------------------------------------------
## bootstrap method
setMethod("mbrBootstrap",
"MBR",
function(object, verbose=TRUE, ...)
{
##---checks
mbr.checks(name="object", para=object)
mbr.checks(name="verbose", para=verbose)
##---get TNIs
TNI1 <- mbrGet(object, what="TNI1")
TNI2 <- mbrGet(object, what="TNI2")
##---bootstrap TNIs
if(verbose) cat("-Performing bootstrap analysis for two TNI
objects...\n\n")
TNI1 <- tni.bootstrap(TNI1, verbose=verbose,...=...)
TNI2 <- tni.bootstrap(TNI2, verbose=verbose,...=...)
#---get
tni1_summary <- tni.get(TNI1, what="summary")
tni2_summary <- tni.get(TNI2, what="summary")
mbr_summary <- mbrGet(object, what="summary")
mbr_para <- mbrGet(object, what="para")
#---changes
mbr_para$TNIs$boot <- tni1_summary$para$boot
mbr_summary$TNIs$TNI1 <- tni1_summary$results$tnet
colnames(mbr_summary$TNIs$TNI1) <- c('RE', 'Targets', 'Edges')
mbr_summary$TNIs$TNI2 <- tni2_summary$results$tnet
colnames(mbr_summary$TNIs$TNI2) <- c('RE', 'Targets', 'Edges')
#---set
object <- .mbr.set(name="TNI1", para=TNI1, object=object)
object <- .mbr.set(name="TNI2", para=TNI2, object=object)
object <- .mbr.set(name="statusUpdate", para="Bootstrap", object=object)
object <- .mbr.set(name="para", para=mbr_para, object=object)
object <- .mbr.set(name="summary", para=mbr_summary, object=object)
return(object)
}
)
#' A filter based on the Data Processing Inequality (DPI) algorithm.
#'
#' This function takes an MBR object and computes two transcriptional networks
#' filtered by the data processing inequality algorithm.
#'
#' @param object A processed object of class \linkS4class{MBR} evaluated by
#' the methods
#' \code{\link[RTNduals:mbrPermutation]{mbrPermutation}} and
#' \code{\link[RTNduals:mbrBootstrap]{mbrBootstrap}}.
#' @param verbose A single logical value specifying to display detailed
#' messages (when verbose=TRUE) or not (when verbose=FALSE).
#' @param ... Additional arguments passed to the
#' \code{\link[RTN:tni.dpi.filter]{tni.dpi.filter}} function.
#' @return An \linkS4class{MBR} object with two DPI-filtered mutual information
#' matrices, one in each "TNI" slot.
#' @examples
#' data("dt4rtn", package = "RTN")
#' gexp <- dt4rtn$gexp
#' annot <- dt4rtn$gexpIDs
#' tfs1 <- dt4rtn$tfs[c("IRF8","IRF1","PRDM1","AFF3","E2F3")]
#' tfs2 <- dt4rtn$tfs[c("HCLS1","STAT4","STAT1","LMO4","ZNF552")]
#' ##---mbrPreprocess
#' rmbr <- mbrPreprocess(gexp=gexp, regulatoryElements1 = tfs1,
#' regulatoryElements2=tfs2, gexpIDs=annot)
#' ##---mbrPermutation
#' rmbr <- mbrPermutation(rmbr, nPermutations=10)
#' ##---mbrBootstrap
#' rmbr <- mbrBootstrap(rmbr, nBootstrap=10)
#' ##---mbrDpiFilter
#' rmbr <- mbrDpiFilter(rmbr)
#'
#' @import RTN
#'
#' @import methods
#' @docType methods
#' @rdname mbrDpiFilter-methods
#' @aliases mbrDpiFilter
#' @export
##------------------------------------------------------------------------------
## dpi filter method
setMethod("mbrDpiFilter",
"MBR",
function(object, verbose=TRUE, ...)
{
##---checks
mbr.checks(name="object", para=object)
mbr.checks(name="verbose", para=verbose)
##---get TNIs
TNI1 <- mbrGet(object, what="TNI1")
TNI2 <- mbrGet(object, what="TNI2")
##---Dpi filter TNIs
if(verbose) cat("-Applying dpi filter for two TNI objects...\n")
TNI1 <-tni.dpi.filter(TNI1, verbose=verbose, ...=...)
TNI2 <-tni.dpi.filter(TNI2, verbose=verbose, ...=...)
#---get
tni1_summary <- tni.get(TNI1, what="summary")
tni2_summary <- tni.get(TNI2, what="summary")
mbr_summary <- mbrGet(object, what="summary")
mbr_para <- mbrGet(object, what="para")
#---changes
mbr_para$TNIs$dpi <- tni1_summary$para$dpi
mbr_summary$TNIs$TNI1 <- tni1_summary$results$tnet
colnames(mbr_summary$TNIs$TNI1) <- c('RE', 'Targets', 'Edges')
mbr_summary$TNIs$TNI2 <- tni2_summary$results$tnet
colnames(mbr_summary$TNIs$TNI2) <- c('RE', 'Targets', 'Edges')
#---set
object <- .mbr.set(name="TNI1", para=TNI1, object=object)
object <- .mbr.set(name="TNI2", para=TNI2, object=object)
object <- .mbr.set(name="statusUpdate", para="DPI.filter", object=object)
object <- .mbr.set(name="para", para=mbr_para, object=object)
object <- .mbr.set(name="summary", para=mbr_summary, object=object)
return(object)
}
)
#' Motifs analysis and inference of 'dual regulons'.
#'
#' This function takes an MBR object and compares the shared regulon
#' targets in order to test whether regulon pairs agree on the predicted
#' downstream effects.
#'
#' @param object A processed object of class \linkS4class{MBR} evaluated by the
#' methods \code{\link[RTNduals:mbrPermutation]{mbrPermutation}},
#' \code{\link[RTNduals:mbrBootstrap]{mbrBootstrap}}
#' and \code{\link[RTNduals:mbrDpiFilter]{mbrDpiFilter}}.
#' @param regulatoryElements1 An optional character vector specifying which
#' 'TNI1' regulatory elements should be evaluated. If 'NULL' all regulatory
#' elements will be evaluated.
#' @param regulatoryElements2 An optional character vector specifying which
#' 'TNI2' regulatory elements should be evaluated. If 'NULL' all regulatory
#' elements will be evaluated.
#' @param minRegulonSize A single integer or numeric value specifying the
#' minimum number of elements in a regulon. Gene sets with fewer than this
#' number are removed from the analysis.
#' @param prob A quantile filter applyed to the association metric used to
#' infer 'dual regulons'.
#' @param estimator A character value specifying the estimator used in the
#' association analysis. One of "spearman" (default), "kendall", or "pearson",
#' can be abbreviated.
#' @param pAdjustMethod A single character value specifying the p-value
#' adjustment method to be used (see 'p.adjust' for details).
#' @param verbose A single logical value specifying to display detailed
#' messages (when verbose=TRUE) or not (when verbose=FALSE).
#' @return An \linkS4class{MBR} object with two data.frames in the slot
#' 'results' listing the inferred 'dual regulons' and a hypergeometric test
#' for each 'dual regulon'.
#' @examples
#' data("dt4rtn", package = "RTN")
#' gexp <- dt4rtn$gexp
#' annot <- dt4rtn$gexpIDs
#' tfs1 <- dt4rtn$tfs[c("IRF8","IRF1","PRDM1","AFF3","E2F3")]
#' tfs2 <- dt4rtn$tfs[c("HCLS1","STAT4","STAT1","LMO4","ZNF552")]
#' ##---mbrPreprocess
#' rmbr <- mbrPreprocess(gexp=gexp, regulatoryElements1 = tfs1,
#' regulatoryElements2=tfs2, gexpIDs=annot)
#' ##---mbrPermutation
#' rmbr <- mbrPermutation(rmbr, nPermutations=10)
#' ##---mbrBootstrap
#' rmbr <- mbrBootstrap(rmbr, nBootstrap=10)
#' ##---mbrDpiFilter
#' rmbr <- mbrDpiFilter(rmbr)
#' ##---mbrAssociation
#' rmbr <- mbrAssociation(rmbr, prob=0.75)
#'
#' @import RTN
#' @importFrom stats p.adjust phyper
#' @importFrom stats cor quantile
#'
#' @import methods
#' @docType methods
#' @rdname mbrAssociation-methods
#' @aliases mbrAssociation
#' @export
##------------------------------------------------------------------------------
##Inference of duals
setMethod("mbrAssociation",
"MBR",
function(object, regulatoryElements1=NULL, regulatoryElements2=NULL,
minRegulonSize=30, prob=0.95,
estimator='spearman', pAdjustMethod="BH", verbose=TRUE)
{
##---gets
TNI1 <- mbrGet(object, what="TNI1")
tni1_gexp <- tni.get(TNI1, what="gexp")
tni1_para <- tni.get(TNI1, what="para")
TNI2 <- mbrGet(object, what="TNI2")
##---checks
mbr.checks(name="minRegulonSize", para=minRegulonSize)
mbr.checks(name="prob", para=prob)
mbr.checks(name="estimator", para=estimator)
mbr.checks(name="pAdjustMethod", para=pAdjustMethod)
mbr.checks(name="verbose", para=verbose)
if(is.null(regulatoryElements1))
{
if(verbose)
cat("-Selecting regulatory elements from TNI1 object...\n")
regulatoryElements1 <- tni.get(TNI1, "tfs")
} else
{
regulatoryElements1 <- .checkRegel(TNI1,
regulatoryElements1)
}
if(is.null(regulatoryElements2))
{
if(verbose)
cat("-Selecting regulatory elements from TNI2 object...\n")
regulatoryElements2 <- tni.get(TNI2, "tfs")
} else
{
regulatoryElements2 <- .checkRegel(TNI2,
regulatoryElements2)
}
mbr.checks(name="regulatoryElements",
para=c(regulatoryElements1, regulatoryElements2))
mbr.checks(name="numberRegElements",
para=c(regulatoryElements1, regulatoryElements2))
##-----get regulons
what <- "refregulons.and.mode"
##if (tnet=="dpi") what <- "regulons.and.mode"
regulons1 <- tni.get(TNI1, what=what)
regulons2 <- tni.get(TNI2, what=what)
##-----get regulatory elements
regulons1 <- regulons1[regulatoryElements1]
regulons2 <- regulons2[regulatoryElements2]
##-----get regulons by min size
size1 <- unlist(lapply(regulons1, length))
idx <- size1 >= (minRegulonSize)
regulons1 <- regulons1[idx]
regulatoryElements1 <- regulatoryElements1[idx]
size1 <- size1[idx]
##---
size2 <- unlist(lapply(regulons2, length))
idx <- size2 >= (minRegulonSize)
regulons2 <- regulons2[idx]
regulatoryElements2 <- regulatoryElements2[idx]
size2 <- size2[idx]
##-----group regulons and regulatory element
regulons <- c(regulons1, regulons2)
regel <- c(regulatoryElements1, regulatoryElements2)
##-----Correlation
tnet <- .regMatrix(regulons, regel, getNames=FALSE)
tbmi <- tnet
##-----
tnet <- .tni.cor(tni1_gexp, tnet, estimator=estimator,
dg=0, asInteger=FALSE,
mapAssignedAssociation=TRUE)
regcor <- cor(tnet[, regulatoryElements1],
tnet[, regulatoryElements2], method=estimator)
##-----
rownames(regcor) <- names(regulatoryElements1)
colnames(regcor) <- names(regulatoryElements2)
##-----select motifs based on 'prob' quantile
if(verbose)
cat(paste("-Getting duals in probs >", prob, "...\n",
sep = ""))
pvlist <- .motifsquantile(regcor=regcor, th=prob)
if(nrow(pvlist) > 0)
{
##-----Mutual Information
pvlist <- .getMIorP(pvlist, regel, tbmi, size1, size2)
##----PadjustValue
if(!is.null(TNI1@results$adjpv))
{
tbpValue <- TNI1@results$adjpv
cutoff <- tni1_para$perm$pValueCutoff
pvlist <- .getMIorP(pvlist, regel, tbpValue, size1, size2,
mutualInformation=FALSE, cutoff=cutoff)
}
##-----Jaccard
pvlist <- .jcOverlap(pvlist, regel, tbmi)
##-----Hypergeometric
##tni1 <- mbrGet(object, what="TNI1")
universe <- rownames(tni1_gexp)
hyperresults <- .mbr.hyper(pvlist=pvlist, regulons=regulons,
regel=regel, universe=universe,
pAdjustMethod=pAdjustMethod,
verbose=verbose)
pvlist$Hypergeometric.Adjusted.Pvalue <- hyperresults$Adjusted.Pvalue
pvlist$Hypergeometric.Pvalue <- hyperresults$Pvalue
}else
{
warning("No 'dual' has been found for the input parameters.")
}
##-----organize pvlist
if("MI.Adjusted.Pvalue"%in%colnames(pvlist))
{
pvlist <- pvlist[,c("Regulon1","Size.Regulon1","Regulon2",
"Size.Regulon2","Jaccard.coefficient",
"Hypergeometric.Pvalue",
"Hypergeometric.Adjusted.Pvalue",
"MI","MI.Adjusted.Pvalue","R","Quantile")]
} else
{
pvlist <- pvlist[,c("Regulon1","Size.Regulon1","Regulon2",
"Size.Regulon2","Jaccard.coefficient",
"Hypergeometric.Pvalue",
"Hypergeometric.Adjusted.Pvalue",
"MI","R","Quantile")]
}
##-----para
mbr_para <- mbrGet(object,what="para")
sum.info.par <- c(minRegulonSize, prob, estimator)
mbr_para$MBR$association['Parameter', ] <- sum.info.par
##---
mbr_summary <- mbrGet(object, what="summary")
info.summary.results <- nrow(pvlist)
mbr_summary$MBR$Duals['duals',] <- info.summary.results
##-----set
object <- .mbr.set(name="statusUpdate",
para="Association", object=object)
object <- .mbr.set(name="para",
para=mbr_para, object=object)
object <- .mbr.set(name="summary",
para=mbr_summary, object=object)
object <- .mbr.set(name="testedElementsTNI1",
para=regulatoryElements1, object=object)
object <- .mbr.set(name="testedElementsTNI2",
para=regulatoryElements2, object=object)
object <- .mbr.set(name="dualRegulons",
para=rownames(pvlist), object=object)
object <- .mbr.set(name="motifsInformation",
para=pvlist, object=object)
object <- .mbr.set(name="hypergeometricResults",
para=hyperresults, object=object)
return(object)
}
)
#' A summary for results from the MBR methods.
#'
#' This function lists the inferred 'dual regulons' and, if available,
#' adds external evidences.
#'
#' @param object A processed object of class \linkS4class{MBR} evaluated by the
#' method \code{\link[RTNduals:mbrAssociation]{mbrAssociation}}.
#' @param supplementary.table An optional 'data.frame' with three columns
#' representing
#' (1) regulatory elements of 'TNI1', (2) regulatory elements of 'TNI2', and
#' (3) external evidences between the regulatory elements.
#' @param evidenceColname A single character value specifying a column in
#' the 'supplementary.table'.
#' @param verbose A single logical value specifying to display detailed
#' messages (when verbose=TRUE) or not (when verbose=FALSE).
#' @return An \linkS4class{MBR} object with a data.frame in the slot 'results'
#' listing the input additional evidences.
#' @examples
#' data("dt4rtn", package = "RTN")
#' gexp <- dt4rtn$gexp
#' annot <- dt4rtn$gexpIDs
#' tfs1 <- dt4rtn$tfs[c("IRF8","IRF1","PRDM1","AFF3","E2F3")]
#' tfs2 <- dt4rtn$tfs[c("HCLS1","STAT4","STAT1","LMO4","ZNF552")]
#' ##---mbrPreprocess
#' rmbr <- mbrPreprocess(gexp=gexp, regulatoryElements1 = tfs1,
#' regulatoryElements2=tfs2, gexpIDs=annot)
#' ##---mbrPermutation
#' rmbr <- mbrPermutation(rmbr, nPermutations=10)
#' ##---mbrBootstrap
#' rmbr <- mbrBootstrap(rmbr, nBootstrap=10)
#' ##---mbrDpiFilter
#' rmbr <- mbrDpiFilter(rmbr)
#' ##---mbrAssociation
#' rmbr <- mbrAssociation(rmbr, prob=0.75)
#' ##---a 'toy' table with supplementary evidences
#' motifsInformation <- mbrGet(rmbr, what="motifsInformation")
#' n <- nrow(motifsInformation)
#' supplementaryTable <- motifsInformation[1:n,c("Regulon1","Regulon2")]
#' supplementaryTable$ToyEvidence <- rnorm(n)
#' ##---mbrDuals
#' rmbr <- mbrDuals(rmbr, supplementary.table = supplementaryTable,
#' evidenceColname = "ToyEvidence")
#' ##---motifsInformation with 'Evidence'
#' motifsInformation <- mbrGet(rmbr, what="motifsInformation")
#' head(motifsInformation)
#'
#' @importFrom utils setTxtProgressBar txtProgressBar
#' @import methods
#' @docType methods
#' @rdname mbrDuals-methods
#' @aliases mbrDuals
#' @export
##------------------------------------------------------------------------------
##organize duals
setMethod( "mbrDuals",
"MBR",
function(object, supplementary.table=NULL, evidenceColname,
verbose=TRUE)
{
##---checks
mbr.checks(name="object", para=object)
##---
motifsInformation <- mbrGet(object, what="motifsInformation")
if(is.null(dim(motifsInformation)))
stop("'motifsInformation' seems null!")
if(verbose) cat("-Sorting by the R value...\n")
idx <- sort(abs(motifsInformation[,"R"]), decreasing=TRUE,
index.return=TRUE)
motifsInformation <- motifsInformation[idx$ix, ]
#---set
object <- .mbr.set(name="motifsInformation",
para=motifsInformation, object=object)
object <- .mbr.set(name="dualRegulons",
para=rownames(motifsInformation), object=object)
if(!is.null(supplementary.table))
{
##---checks
if(missing(evidenceColname))
stop("'evidenceColname' should be a character value present in
colnames of supplementary.table!")
mbr.checks(name="supplementary.table", para=supplementary.table)
mbr.checks(name="uniqueInput", para=supplementary.table)
mbr.checks(name="evidenceColname", para=evidenceColname)
##---consistency
if(verbose)
cat("-Checking the 'supplementary.table' consistency...\n")
supplementary.table <- .consisSuppTable(object,
supplementary.table,
evidenceColname,
verbose=verbose)
##---find duals
object <- .checkLoops(object, supplementary.table,
evidenceColname, verbose=verbose)
}
return(object)
}
)
#' A preprocessing function for objects of class MBR.
#'
#' This function merges two TNI class objects and creates one MBR class object.
#'
#' @param tni1 A 'TNI' class object.
#' @param tni2 Another 'TNI' class object
#' @param verbose A single logical value specifying to display detailed messages
#' (when verbose=TRUE) or not (when verbose=FALSE).
#' @return An \linkS4class{MBR} object.
#' @examples
#' data("dt4rtn", package = "RTN")
#' gexp <- dt4rtn$gexp
#' annot <- dt4rtn$gexpIDs
#' tfs1 <- dt4rtn$tfs[c("IRF8","IRF1","PRDM1","AFF3","E2F3")]
#' tfs2 <- dt4rtn$tfs[c("HCLS1","STAT4","STAT1","LMO4","ZNF552")]
#' ##---mbrPreprocess
#' rmbr <- mbrPreprocess(gexp=gexp, regulatoryElements1 = tfs1,
#' regulatoryElements2=tfs2, gexpIDs=annot)
#' ##---mbrPermutation
#' rmbr <- mbrPermutation(rmbr, nPermutations=10)
#' ##---mbrBootstrap
#' rmbr <- mbrBootstrap(rmbr, nBootstrap=10)
#' rmbr <- mbrDpiFilter(rmbr)
#' ##---tni2mbrPreprocess
#' tni1 <- mbrGet(rmbr, what="TNI1")
#' tni2 <- mbrGet(rmbr, what="TNI2")
#' rmbr <- tni2mbrPreprocess(tni1, tni2)
#'
#' @import methods
#' @docType methods
#' @rdname tni2mbrPreprocess-methods
#' @aliases tni2mbrPreprocess
#' @export
##------------------------------------------------------------------------------
##Combine two TNIs produced separately
setMethod("tni2mbrPreprocess",
"TNI",
function (tni1, tni2, verbose=TRUE)
{
if(missing(tni1)) stop("NOTE: 'tni1' is missing ", call.=FALSE)
if(missing(tni2)) stop("NOTE: 'tni2' is missing ", call.=FALSE)
mbr.checks (name='tni', para=tni1)
mbr.checks (name='tni', para=tni2)
.combineTNIs (tni1=tni1, tni2=tni2, verbose=verbose)
#---get
gexp <- tni.get(tni1, what="gexp")
regulatoryElements1 <- tni.get(tni1, what="tfs")
regulatoryElements2 <- tni.get(tni2, what="tfs")
##---- creates MBR object
object <- .MBRmaker(class="MBR", gexp=gexp,
regulatoryElements1=regulatoryElements1,
regulatoryElements2=regulatoryElements2)
#---TNIs Update
object <- .mbr.set(name="TNI1", para=tni1, object=object)
object <- .mbr.set(name="TNI2", para=tni2, object=object)
#---statu update
tni_status <- tni.get(tni1, what="status")
status <- names(tni_status[tni_status=="[x]"])
object <- .mbr.set(name="statusUpdate", para=status, object=object)
#---get Updates
tni1_summary <- tni.get(tni1, what="summary")
tni2_summary <- tni.get(tni2, what="summary")
mbr_summary <- mbrGet(object, what="summary")
mbr_para <- mbrGet(object, what="para")
##---permutation
mbr_para$TNIs$perm <- tni1_summary$para$perm
mbr_summary$TNIs$TNI1 <- tni1_summary$results$tnet
colnames(mbr_summary$TNIs$TNI1) <- c('RE', 'Targets', 'Edges')
mbr_summary$TNIs$TNI2 <- tni2_summary$results$tnet
colnames(mbr_summary$TNIs$TNI2) <- c('RE', 'Targets', 'Edges')
##---bootstrap
mbr_para$TNIs$boot <- tni1_summary$para$boot
mbr_summary$TNIs$TNI1 <- tni1_summary$results$tnet
colnames(mbr_summary$TNIs$TNI1) <- c('RE', 'Targets', 'Edges')
mbr_summary$TNIs$TNI2 <- tni2_summary$results$tnet
colnames(mbr_summary$TNIs$TNI2) <- c('RE', 'Targets', 'Edges')
##---summary dpi.filter
mbr_para$TNIs$dpi <- tni1_summary$para$dpi
mbr_summary$TNIs$TNI1 <- tni1_summary$results$tnet
colnames(mbr_summary$TNIs$TNI1) <- c('RE', 'Targets', 'Edges')
mbr_summary$TNIs$TNI2 <- tni2_summary$results$tnet
colnames(mbr_summary$TNIs$TNI2) <- c('RE', 'Targets', 'Edges')
#---set
object <- .mbr.set(name="para", para=mbr_para, object=object)
object <- .mbr.set(name="summary", para=mbr_summary, object=object)
return (object)
}
)
##------------------------------------------------------------------------------
##show summary information on screen
setMethod( "show",
"MBR",
function(object)
{
cat("an MBR (Motifs Between Regulons) object:\n")
message("--status:")
print(object@status, quote=FALSE)
}
)
#' Get information from individual slots in MBR object.
#'
#' Get information from individual slots in an MBR object and any available
#' results from previous analysis.
#'
#' @param object A preprocessed object of class \linkS4class{MBR}
#' @param what a single character value specifying which information should be
#' retrieved from the slots. Options: "TNI1", "TNI2", "testedElementsTNI1",
#' "testedElementsTNI2", "dualRegulons", "results", "para", "summary",
#' "status", "motifsInformation" and "hyperResults"
#' @return A slot content from a object of class 'MBR' \linkS4class{MBR} object
#' @examples
#' data("dt4rtn", package = "RTN")
#' gexp <- dt4rtn$gexp
#' annot <- dt4rtn$gexpIDs
#' tfs1 <- dt4rtn$tfs[c("IRF8","IRF1","PRDM1","AFF3","E2F3")]
#' tfs2 <- dt4rtn$tfs[c("HCLS1","STAT4","STAT1","LMO4","ZNF552")]
#' ##---mbrPreprocess
#' rmbr <- mbrPreprocess(gexp=gexp, regulatoryElements1 = tfs1,
#' regulatoryElements2=tfs2, gexpIDs=annot)
#' ##---get the 'TNI1' slot using 'mbrGet'
#' tni1 <- mbrGet(rmbr, what="TNI1")
#'
#' @import methods
#' @docType methods
#' @rdname mbrGet-methods
#' @aliases mbrGet
#' @export
##------------------------------------------------------------------------------
##get slots from MBR object
setMethod( "mbrGet",
"MBR",
function(object, what="status")
{
##---check input arguments
mbr.checks(name="object", para=object)
mbr.checks(name="mbrGet", para=what)
##---Association options any change needs update!
optsAssoci <- c("testedElementsTNI1", "testedElementsTNI2",
"dualRegulons", "motifsInformation", "results",
"hyperResults")
##---get query
if(what=="TNI1")
{
query <- object@TNI1
}
else if(what=="TNI2")
{
query <- object@TNI2
}
else if(what=="para")
{
query <- object@para
}
else if(what=="summary")
{
query <- object@summary
}
else if(what=="status")
{
query <- object@status
}
else if(what%in%optsAssoci)
{
if(object@status["Association"] != "[x]")
{
warning("NOTE: input 'object' needs 'mbrAssociation'
evaluation!")
query <- NULL
} else {
if(what=="testedElementsTNI1")
{
query <- object@testedElementsTNI1
}
else if(what=="testedElementsTNI2")
{
query <- object@testedElementsTNI2
}
else if(what=="dualRegulons")
{
query <- object@dualRegulons
}
else if(what=="results")
{
query <- object@results
}
else if(what=="motifsInformation")
{
query <- object@results$motifsInformation
}
else if(what=="hyperResults")
{
query <- object@results$hypergeometricResults
}
}
}
return(query)
}
)
chagasVinicius/RTNmotifs documentation built on May 13, 2019, 3:10 p.m.
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################################################################################
########################## MBR-methods ############################
################################################################################
##------------------------------------------------------------------------------
#########################################
###class builder
#########################################
.MBRmaker <-
function(class="MBR", gexp=gexp,
regulatoryElements1=regulatoryElements1,
regulatoryElements2=regulatoryElements2)
{
#---creates the 'MBR' object
object <- newMBR(class=class, gexp=gexp,
regulatoryElements1=regulatoryElements1,
regulatoryElements2=regulatoryElements2,
TNI1=NULL, TNI2=NULL,
testedElementsTNI1=character(),
testedElementsTNI2=character(),
dualRegulons=character(),
results=list(), para=list(), summary=list(),
status=character())
#---status
status <- rep('[ ]', 1, 5)
names(status) <- c('Preprocess', 'Permutation',
'Bootstrap', 'DPI.filter',
'Association')
#---parameters
sum.info.para <- list()
sum.info.para$TNIs$perm <- NA
sum.info.para$TNIs$boot <- NA
sum.info.para$TNIs$dpi <- NA
sum.info.para$MBR$association <- matrix(NA, 1, 3)
colnames(sum.info.para$MBR$association) <- c('minRegulonSize',
'prob',
'estimator')
rownames(sum.info.para$MBR$association) <- 'Parameter'
#---summary motifsInformation
sum.info.summary <- list()
sum.info.summary$MBR$Duals <- matrix(NA, 1, 1)
colnames(sum.info.summary$MBR$Duals) <- 'numberDuals'
rownames(sum.info.summary$MBR$Duals) <- 'duals'
#---set
object <- .mbr.set(name="status", para=status, object=object)
object <- .mbr.set(name="para", para=sum.info.para, object=object)
object <- .mbr.set(name="summary", para=sum.info.summary, object=object)
return(object)
}
#----------------------------------------------------------
#it creates the 'MBR' class object
newMBR <-
function(class, gexp, regulatoryElements1, regulatoryElements2,
TNI1, TNI2, testedElementsTNI1, testedElementsTNI2,
dualRegulons, results, para, summary, status)
{
#---checks
if(missing(gexp)) stop("NOTE: 'gexp' is missing ", call.=FALSE)
if(missing(regulatoryElements1))
stop("NOTE: 'regulatoryElements1' is missing", call.=FALSE)
if(missing(regulatoryElements2))
stop("NOTE: 'regulatoryElements2' is missing", call.=FALSE)
mbr.checks(name='TNI', TNI1)
mbr.checks(name='TNI', TNI2)
mbr.checks(name='testedElementsTNI', testedElementsTNI1)
mbr.checks(name='testedElementsTNI', testedElementsTNI2)
mbr.checks(name='dualRegulons', dualRegulons)
mbr.checks(name='results', results)
mbr.checks(name='para', para)
mbr.checks(name='summary', summary)
mbr.checks(name='status', status)
mbr.checks(name='gexp', gexp)
mbr.checks(name='regulatoryElements1', regulatoryElements1)
mbr.checks(name='regulatoryElements2', regulatoryElements2)
#---creating TNIs
regulonsTNI1 <- new("TNI", gexp=gexp,
transcriptionFactors=regulatoryElements1)
regulonsTNI2 <- new("TNI", gexp=gexp,
transcriptionFactors=regulatoryElements2)
#---creating the MBR-object
new(class, TNI1=regulonsTNI1, TNI2=regulonsTNI2,
testedElementsTNI1=testedElementsTNI1,
testedElementsTNI2=testedElementsTNI2,
dualRegulons=dualRegulons, results=results,
para=para, summary=summary, status=status)
}
##------------------------------------------------------------------------------
#' A preprocessing function for objects of class MBR.
#'
#' @param gexp A numerical matrix, typically with mRNA and/or miRNA expression
#' values.
#' @param regulatoryElements1 A named vector with regulatory elements listed in
#' 'gexp' rownames.
#' @param regulatoryElements2 A named vector with regulatory elements listed in
#' 'gexp' rownames.
#' @param verbose A single logical value specifying to display detailed
#' messages (when verbose=TRUE) or not (when verbose=FALSE).
#' @param ... Additional arguments passed on to
#' \code{\link[RTN:tni.preprocess]{tni.preprocess}} function.
#' @return A preprocessed 'MBR-class' object.
#' @examples
#' data("dt4rtn", package = "RTN")
#' gexp <- dt4rtn$gexp
#' annot <- dt4rtn$gexpIDs
#' tfs1 <- dt4rtn$tfs[c("IRF8","IRF1","PRDM1","AFF3","E2F3")]
#' tfs2 <- dt4rtn$tfs[c("HCLS1","STAT4","STAT1","LMO4","ZNF552")]
#' ##---mbrPreprocess
#' rmbr <- mbrPreprocess(gexp=gexp, regulatoryElements1 = tfs1,
#' regulatoryElements2=tfs2, gexpIDs=annot)
#'
#' @import RTN
#'
#' @import methods
#' @docType methods
#' @rdname mbrPreprocess-methods
#' @aliases mbrPreprocess
#' @export
##Regulons pre-processing method
setMethod("mbrPreprocess",
"matrix",
function(gexp, regulatoryElements1, regulatoryElements2,
verbose=TRUE,...)
{
##---
mbr.checks(name="verbose", para=verbose)
object <- .MBRmaker(class="MBR", gexp=gexp,
regulatoryElements1=regulatoryElements1,
regulatoryElements2=regulatoryElements2)
##---get TNIs
TNI1 <- mbrGet(object, what="TNI1")
TNI2 <- mbrGet(object, what="TNI2")
##---pre-processing TNIs
if(verbose) cat("-Preprocessing TNI objects...\n\n")
TNI1 <- tni.preprocess(TNI1, verbose=verbose,...=...)
TNI2 <- tni.preprocess(TNI2, verbose=verbose,...=...)
tfs1 <- tni.get(TNI1, what="tfs")
tfs2 <- tni.get(TNI2, what="tfs")
mbr.checks(name="regulatoryElements",
para=c(tfs1,tfs2))
##---set
object <- .mbr.set(name="TNI1", para=TNI1, object=object)
object <- .mbr.set(name="TNI2", para=TNI2, object=object)
object <- .mbr.set(name="statusUpdate",
para="Preprocess", object=object)
return(object)
}
)
##------------------------------------------------------------------------------
#' Inference of transcriptional networks.
#'
#' This function takes an MBR object and computes two transcriptional networks
#' inferred
#' by mutual information (with multiple hypothesis testing corrections).
#'
#' @param object A preprocessed object of class \linkS4class{MBR}.
#' @param verbose A single logical value specifying to display detailed
#' messages (when verbose=TRUE) or not (when verbose=FALSE).
#' @param ... Additional arguments passed on to the
#' \code{\link[RTN:tni.permutation]{tni.permutation}} function.
#' @return An \linkS4class{MBR} object with two mutual information matrices,
#' one in each "TNI" slot.
#' @examples
#' data("dt4rtn", package = "RTN")
#' gexp <- dt4rtn$gexp
#' annot <- dt4rtn$gexpIDs
#' tfs1 <- dt4rtn$tfs[c("IRF8","IRF1","PRDM1","AFF3","E2F3")]
#' tfs2 <- dt4rtn$tfs[c("HCLS1","STAT4","STAT1","LMO4","ZNF552")]
#' ##---mbrPreprocess
#' rmbr <- mbrPreprocess(gexp=gexp, regulatoryElements1 = tfs1,
#' regulatoryElements2=tfs2, gexpIDs=annot)
#' ##---mbrPermutation
#' rmbr <- mbrPermutation(rmbr, nPermutations=10)
#'
#' @import RTN
#'
#' @import methods
#' @docType methods
#' @rdname mbrPermutation-methods
#' @aliases mbrPermutation
#' @export
## permutation
setMethod("mbrPermutation",
"MBR",
function(object, verbose=TRUE, ...)
{
##---checks
mbr.checks(name="object", para=object)
mbr.checks(name="verbose", para=verbose)
##---get TNIs
TNI1 <- mbrGet(object, what="TNI1")
TNI2 <- mbrGet(object, what="TNI2")
##---permutation TNIs
if(verbose)
cat("-Performing permutation analysis for two TNI objects...\n\n")
TNI1 <- tni.permutation(TNI1, verbose=verbose,...=...)
TNI2 <- tni.permutation(TNI2, verbose=verbose,...=...)
#---get
tni1_summary <- tni.get(TNI1, what="summary")
tni2_summary <- tni.get(TNI2, what="summary")
mbr_summary <- mbrGet(object, what="summary")
mbr_para <- mbrGet(object, what="para")
#---changes
mbr_para$TNIs$perm <- tni1_summary$para$perm
mbr_summary$TNIs$TNI1 <- tni1_summary$results$tnet
colnames(mbr_summary$TNIs$TNI1) <- c('RE', 'Targets', 'Edges')
mbr_summary$TNIs$TNI2 <- tni2_summary$results$tnet
colnames(mbr_summary$TNIs$TNI2) <- c('RE', 'Targets', 'Edges')
#---set
object <- .mbr.set(name="TNI1", para=TNI1, object=object)
object <- .mbr.set(name="TNI2", para=TNI2, object=object)
object <- .mbr.set(name="statusUpdate",
para="Permutation", object=object)
object <- .mbr.set(name="para", para=mbr_para, object=object)
object <- .mbr.set(name="summary", para=mbr_summary, object=object)
return(object)
}
)
#' Inference of consensus transcriptional networks.
#'
#' This function takes an MBR object and computes two consensus transcriptional
#' networks.
#'
#' @param object A processed objec of class \linkS4class{MBR} evaluated by the
#' method \code{\link[RTNduals:mbrPermutation]{mbrPermutation}}.
#' @param verbose A single logical value specifying to display detailed
#' messages (when verbose=TRUE) or not (when verbose=FALSE).
#' @param ... Additional arguments passed to the
#' \code{\link[RTN:tni.bootstrap]{tni.bootstrap}} function.
#' @return An \linkS4class{MBR} object with two consensus mutual information
#' matrices, one in each "TNI" slot.
#' @examples
#' data("dt4rtn", package = "RTN")
#' gexp <- dt4rtn$gexp
#' annot <- dt4rtn$gexpIDs
#' tfs1 <- dt4rtn$tfs[c("IRF8","IRF1","PRDM1","AFF3","E2F3")]
#' tfs2 <- dt4rtn$tfs[c("HCLS1","STAT4","STAT1","LMO4","ZNF552")]
#' ##---mbrPreprocess
#' rmbr <- mbrPreprocess(gexp=gexp, regulatoryElements1 = tfs1,
#' regulatoryElements2=tfs2, gexpIDs=annot)
#' ##---mbrPermutation
#' rmbr <- mbrPermutation(rmbr, nPermutations=10)
#' ##---mbrBootstrap
#' rmbr <- mbrBootstrap(rmbr, nBootstrap=10)
#'
#' @import RTN
#'
#' @import methods
#' @docType methods
#' @rdname mbrBootstrap-methods
#' @aliases mbrBootstrap
#' @export
##------------------------------------------------------------------------------
## bootstrap method
setMethod("mbrBootstrap",
"MBR",
function(object, verbose=TRUE, ...)
{
##---checks
mbr.checks(name="object", para=object)
mbr.checks(name="verbose", para=verbose)
##---get TNIs
TNI1 <- mbrGet(object, what="TNI1")
TNI2 <- mbrGet(object, what="TNI2")
##---bootstrap TNIs
if(verbose) cat("-Performing bootstrap analysis for two TNI
objects...\n\n")
TNI1 <- tni.bootstrap(TNI1, verbose=verbose,...=...)
TNI2 <- tni.bootstrap(TNI2, verbose=verbose,...=...)
#---get
tni1_summary <- tni.get(TNI1, what="summary")
tni2_summary <- tni.get(TNI2, what="summary")
mbr_summary <- mbrGet(object, what="summary")
mbr_para <- mbrGet(object, what="para")
#---changes
mbr_para$TNIs$boot <- tni1_summary$para$boot
mbr_summary$TNIs$TNI1 <- tni1_summary$results$tnet
colnames(mbr_summary$TNIs$TNI1) <- c('RE', 'Targets', 'Edges')
mbr_summary$TNIs$TNI2 <- tni2_summary$results$tnet
colnames(mbr_summary$TNIs$TNI2) <- c('RE', 'Targets', 'Edges')
#---set
object <- .mbr.set(name="TNI1", para=TNI1, object=object)
object <- .mbr.set(name="TNI2", para=TNI2, object=object)
object <- .mbr.set(name="statusUpdate", para="Bootstrap", object=object)
object <- .mbr.set(name="para", para=mbr_para, object=object)
object <- .mbr.set(name="summary", para=mbr_summary, object=object)
return(object)
}
)
#' A filter based on the Data Processing Inequality (DPI) algorithm.
#'
#' This function takes an MBR object and computes two transcriptional networks
#' filtered by the data processing inequality algorithm.
#'
#' @param object A processed object of class \linkS4class{MBR} evaluated by
#' the methods
#' \code{\link[RTNduals:mbrPermutation]{mbrPermutation}} and
#' \code{\link[RTNduals:mbrBootstrap]{mbrBootstrap}}.
#' @param verbose A single logical value specifying to display detailed
#' messages (when verbose=TRUE) or not (when verbose=FALSE).
#' @param ... Additional arguments passed to the
#' \code{\link[RTN:tni.dpi.filter]{tni.dpi.filter}} function.
#' @return An \linkS4class{MBR} object with two DPI-filtered mutual information
#' matrices, one in each "TNI" slot.
#' @examples
#' data("dt4rtn", package = "RTN")
#' gexp <- dt4rtn$gexp
#' annot <- dt4rtn$gexpIDs
#' tfs1 <- dt4rtn$tfs[c("IRF8","IRF1","PRDM1","AFF3","E2F3")]
#' tfs2 <- dt4rtn$tfs[c("HCLS1","STAT4","STAT1","LMO4","ZNF552")]
#' ##---mbrPreprocess
#' rmbr <- mbrPreprocess(gexp=gexp, regulatoryElements1 = tfs1,
#' regulatoryElements2=tfs2, gexpIDs=annot)
#' ##---mbrPermutation
#' rmbr <- mbrPermutation(rmbr, nPermutations=10)
#' ##---mbrBootstrap
#' rmbr <- mbrBootstrap(rmbr, nBootstrap=10)
#' ##---mbrDpiFilter
#' rmbr <- mbrDpiFilter(rmbr)
#'
#' @import RTN
#'
#' @import methods
#' @docType methods
#' @rdname mbrDpiFilter-methods
#' @aliases mbrDpiFilter
#' @export
##------------------------------------------------------------------------------
## dpi filter method
setMethod("mbrDpiFilter",
"MBR",
function(object, verbose=TRUE, ...)
{
##---checks
mbr.checks(name="object", para=object)
mbr.checks(name="verbose", para=verbose)
##---get TNIs
TNI1 <- mbrGet(object, what="TNI1")
TNI2 <- mbrGet(object, what="TNI2")
##---Dpi filter TNIs
if(verbose) cat("-Applying dpi filter for two TNI objects...\n")
TNI1 <-tni.dpi.filter(TNI1, verbose=verbose, ...=...)
TNI2 <-tni.dpi.filter(TNI2, verbose=verbose, ...=...)
#---get
tni1_summary <- tni.get(TNI1, what="summary")
tni2_summary <- tni.get(TNI2, what="summary")
mbr_summary <- mbrGet(object, what="summary")
mbr_para <- mbrGet(object, what="para")
#---changes
mbr_para$TNIs$dpi <- tni1_summary$para$dpi
mbr_summary$TNIs$TNI1 <- tni1_summary$results$tnet
colnames(mbr_summary$TNIs$TNI1) <- c('RE', 'Targets', 'Edges')
mbr_summary$TNIs$TNI2 <- tni2_summary$results$tnet
colnames(mbr_summary$TNIs$TNI2) <- c('RE', 'Targets', 'Edges')
#---set
object <- .mbr.set(name="TNI1", para=TNI1, object=object)
object <- .mbr.set(name="TNI2", para=TNI2, object=object)
object <- .mbr.set(name="statusUpdate", para="DPI.filter", object=object)
object <- .mbr.set(name="para", para=mbr_para, object=object)
object <- .mbr.set(name="summary", para=mbr_summary, object=object)
return(object)
}
)
#' Motifs analysis and inference of 'dual regulons'.
#'
#' This function takes an MBR object and compares the shared regulon
#' targets in order to test whether regulon pairs agree on the predicted
#' downstream effects.
#'
#' @param object A processed object of class \linkS4class{MBR} evaluated by the
#' methods \code{\link[RTNduals:mbrPermutation]{mbrPermutation}},
#' \code{\link[RTNduals:mbrBootstrap]{mbrBootstrap}}
#' and \code{\link[RTNduals:mbrDpiFilter]{mbrDpiFilter}}.
#' @param regulatoryElements1 An optional character vector specifying which
#' 'TNI1' regulatory elements should be evaluated. If 'NULL' all regulatory
#' elements will be evaluated.
#' @param regulatoryElements2 An optional character vector specifying which
#' 'TNI2' regulatory elements should be evaluated. If 'NULL' all regulatory
#' elements will be evaluated.
#' @param minRegulonSize A single integer or numeric value specifying the
#' minimum number of elements in a regulon. Gene sets with fewer than this
#' number are removed from the analysis.
#' @param prob A quantile filter applyed to the association metric used to
#' infer 'dual regulons'.
#' @param estimator A character value specifying the estimator used in the
#' association analysis. One of "spearman" (default), "kendall", or "pearson",
#' can be abbreviated.
#' @param pAdjustMethod A single character value specifying the p-value
#' adjustment method to be used (see 'p.adjust' for details).
#' @param verbose A single logical value specifying to display detailed
#' messages (when verbose=TRUE) or not (when verbose=FALSE).
#' @return An \linkS4class{MBR} object with two data.frames in the slot
#' 'results' listing the inferred 'dual regulons' and a hypergeometric test
#' for each 'dual regulon'.
#' @examples
#' data("dt4rtn", package = "RTN")
#' gexp <- dt4rtn$gexp
#' annot <- dt4rtn$gexpIDs
#' tfs1 <- dt4rtn$tfs[c("IRF8","IRF1","PRDM1","AFF3","E2F3")]
#' tfs2 <- dt4rtn$tfs[c("HCLS1","STAT4","STAT1","LMO4","ZNF552")]
#' ##---mbrPreprocess
#' rmbr <- mbrPreprocess(gexp=gexp, regulatoryElements1 = tfs1,
#' regulatoryElements2=tfs2, gexpIDs=annot)
#' ##---mbrPermutation
#' rmbr <- mbrPermutation(rmbr, nPermutations=10)
#' ##---mbrBootstrap
#' rmbr <- mbrBootstrap(rmbr, nBootstrap=10)
#' ##---mbrDpiFilter
#' rmbr <- mbrDpiFilter(rmbr)
#' ##---mbrAssociation
#' rmbr <- mbrAssociation(rmbr, prob=0.75)
#'
#' @import RTN
#' @importFrom stats p.adjust phyper
#' @importFrom stats cor quantile
#'
#' @import methods
#' @docType methods
#' @rdname mbrAssociation-methods
#' @aliases mbrAssociation
#' @export
##------------------------------------------------------------------------------
##Inference of duals
setMethod("mbrAssociation",
"MBR",
function(object, regulatoryElements1=NULL, regulatoryElements2=NULL,
minRegulonSize=30, prob=0.95,
estimator='spearman', pAdjustMethod="BH", verbose=TRUE)
{
##---gets
TNI1 <- mbrGet(object, what="TNI1")
tni1_gexp <- tni.get(TNI1, what="gexp")
tni1_para <- tni.get(TNI1, what="para")
TNI2 <- mbrGet(object, what="TNI2")
##---checks
mbr.checks(name="minRegulonSize", para=minRegulonSize)
mbr.checks(name="prob", para=prob)
mbr.checks(name="estimator", para=estimator)
mbr.checks(name="pAdjustMethod", para=pAdjustMethod)
mbr.checks(name="verbose", para=verbose)
if(is.null(regulatoryElements1))
{
if(verbose)
cat("-Selecting regulatory elements from TNI1 object...\n")
regulatoryElements1 <- tni.get(TNI1, "tfs")
} else
{
regulatoryElements1 <- .checkRegel(TNI1,
regulatoryElements1)
}
if(is.null(regulatoryElements2))
{
if(verbose)
cat("-Selecting regulatory elements from TNI2 object...\n")
regulatoryElements2 <- tni.get(TNI2, "tfs")
} else
{
regulatoryElements2 <- .checkRegel(TNI2,
regulatoryElements2)
}
mbr.checks(name="regulatoryElements",
para=c(regulatoryElements1, regulatoryElements2))
mbr.checks(name="numberRegElements",
para=c(regulatoryElements1, regulatoryElements2))
##-----get regulons
what <- "refregulons.and.mode"
##if (tnet=="dpi") what <- "regulons.and.mode"
regulons1 <- tni.get(TNI1, what=what)
regulons2 <- tni.get(TNI2, what=what)
##-----get regulatory elements
regulons1 <- regulons1[regulatoryElements1]
regulons2 <- regulons2[regulatoryElements2]
##-----get regulons by min size
size1 <- unlist(lapply(regulons1, length))
idx <- size1 >= (minRegulonSize)
regulons1 <- regulons1[idx]
regulatoryElements1 <- regulatoryElements1[idx]
size1 <- size1[idx]
##---
size2 <- unlist(lapply(regulons2, length))
idx <- size2 >= (minRegulonSize)
regulons2 <- regulons2[idx]
regulatoryElements2 <- regulatoryElements2[idx]
size2 <- size2[idx]
##-----group regulons and regulatory element
regulons <- c(regulons1, regulons2)
regel <- c(regulatoryElements1, regulatoryElements2)
##-----Correlation
tnet <- .regMatrix(regulons, regel, getNames=FALSE)
tbmi <- tnet
##-----
tnet <- .tni.cor(tni1_gexp, tnet, estimator=estimator,
dg=0, asInteger=FALSE,
mapAssignedAssociation=TRUE)
regcor <- cor(tnet[, regulatoryElements1],
tnet[, regulatoryElements2], method=estimator)
##-----
rownames(regcor) <- names(regulatoryElements1)
colnames(regcor) <- names(regulatoryElements2)
##-----select motifs based on 'prob' quantile
if(verbose)
cat(paste("-Getting duals in probs >", prob, "...\n",
sep = ""))
pvlist <- .motifsquantile(regcor=regcor, th=prob)
if(nrow(pvlist) > 0)
{
##-----Mutual Information
pvlist <- .getMIorP(pvlist, regel, tbmi, size1, size2)
##----PadjustValue
if(!is.null(TNI1@results$adjpv))
{
tbpValue <- TNI1@results$adjpv
cutoff <- tni1_para$perm$pValueCutoff
pvlist <- .getMIorP(pvlist, regel, tbpValue, size1, size2,
mutualInformation=FALSE, cutoff=cutoff)
}
##-----Jaccard
pvlist <- .jcOverlap(pvlist, regel, tbmi)
##-----Hypergeometric
##tni1 <- mbrGet(object, what="TNI1")
universe <- rownames(tni1_gexp)
hyperresults <- .mbr.hyper(pvlist=pvlist, regulons=regulons,
regel=regel, universe=universe,
pAdjustMethod=pAdjustMethod,
verbose=verbose)
pvlist$Hypergeometric.Adjusted.Pvalue <- hyperresults$Adjusted.Pvalue
pvlist$Hypergeometric.Pvalue <- hyperresults$Pvalue
}else
{
warning("No 'dual' has been found for the input parameters.")
}
##-----organize pvlist
if("MI.Adjusted.Pvalue"%in%colnames(pvlist))
{
pvlist <- pvlist[,c("Regulon1","Size.Regulon1","Regulon2",
"Size.Regulon2","Jaccard.coefficient",
"Hypergeometric.Pvalue",
"Hypergeometric.Adjusted.Pvalue",
"MI","MI.Adjusted.Pvalue","R","Quantile")]
} else
{
pvlist <- pvlist[,c("Regulon1","Size.Regulon1","Regulon2",
"Size.Regulon2","Jaccard.coefficient",
"Hypergeometric.Pvalue",
"Hypergeometric.Adjusted.Pvalue",
"MI","R","Quantile")]
}
##-----para
mbr_para <- mbrGet(object,what="para")
sum.info.par <- c(minRegulonSize, prob, estimator)
mbr_para$MBR$association['Parameter', ] <- sum.info.par
##---
mbr_summary <- mbrGet(object, what="summary")
info.summary.results <- nrow(pvlist)
mbr_summary$MBR$Duals['duals',] <- info.summary.results
##-----set
object <- .mbr.set(name="statusUpdate",
para="Association", object=object)
object <- .mbr.set(name="para",
para=mbr_para, object=object)
object <- .mbr.set(name="summary",
para=mbr_summary, object=object)
object <- .mbr.set(name="testedElementsTNI1",
para=regulatoryElements1, object=object)
object <- .mbr.set(name="testedElementsTNI2",
para=regulatoryElements2, object=object)
object <- .mbr.set(name="dualRegulons",
para=rownames(pvlist), object=object)
object <- .mbr.set(name="motifsInformation",
para=pvlist, object=object)
object <- .mbr.set(name="hypergeometricResults",
para=hyperresults, object=object)
return(object)
}
)
#' A summary for results from the MBR methods.
#'
#' This function lists the inferred 'dual regulons' and, if available,
#' adds external evidences.
#'
#' @param object A processed object of class \linkS4class{MBR} evaluated by the
#' method \code{\link[RTNduals:mbrAssociation]{mbrAssociation}}.
#' @param supplementary.table An optional 'data.frame' with three columns
#' representing
#' (1) regulatory elements of 'TNI1', (2) regulatory elements of 'TNI2', and
#' (3) external evidences between the regulatory elements.
#' @param evidenceColname A single character value specifying a column in
#' the 'supplementary.table'.
#' @param verbose A single logical value specifying to display detailed
#' messages (when verbose=TRUE) or not (when verbose=FALSE).
#' @return An \linkS4class{MBR} object with a data.frame in the slot 'results'
#' listing the input additional evidences.
#' @examples
#' data("dt4rtn", package = "RTN")
#' gexp <- dt4rtn$gexp
#' annot <- dt4rtn$gexpIDs
#' tfs1 <- dt4rtn$tfs[c("IRF8","IRF1","PRDM1","AFF3","E2F3")]
#' tfs2 <- dt4rtn$tfs[c("HCLS1","STAT4","STAT1","LMO4","ZNF552")]
#' ##---mbrPreprocess
#' rmbr <- mbrPreprocess(gexp=gexp, regulatoryElements1 = tfs1,
#' regulatoryElements2=tfs2, gexpIDs=annot)
#' ##---mbrPermutation
#' rmbr <- mbrPermutation(rmbr, nPermutations=10)
#' ##---mbrBootstrap
#' rmbr <- mbrBootstrap(rmbr, nBootstrap=10)
#' ##---mbrDpiFilter
#' rmbr <- mbrDpiFilter(rmbr)
#' ##---mbrAssociation
#' rmbr <- mbrAssociation(rmbr, prob=0.75)
#' ##---a 'toy' table with supplementary evidences
#' motifsInformation <- mbrGet(rmbr, what="motifsInformation")
#' n <- nrow(motifsInformation)
#' supplementaryTable <- motifsInformation[1:n,c("Regulon1","Regulon2")]
#' supplementaryTable$ToyEvidence <- rnorm(n)
#' ##---mbrDuals
#' rmbr <- mbrDuals(rmbr, supplementary.table = supplementaryTable,
#' evidenceColname = "ToyEvidence")
#' ##---motifsInformation with 'Evidence'
#' motifsInformation <- mbrGet(rmbr, what="motifsInformation")
#' head(motifsInformation)
#'
#' @importFrom utils setTxtProgressBar txtProgressBar
#' @import methods
#' @docType methods
#' @rdname mbrDuals-methods
#' @aliases mbrDuals
#' @export
##------------------------------------------------------------------------------
##organize duals
setMethod( "mbrDuals",
"MBR",
function(object, supplementary.table=NULL, evidenceColname,
verbose=TRUE)
{
##---checks
mbr.checks(name="object", para=object)
##---
motifsInformation <- mbrGet(object, what="motifsInformation")
if(is.null(dim(motifsInformation)))
stop("'motifsInformation' seems null!")
if(verbose) cat("-Sorting by the R value...\n")
idx <- sort(abs(motifsInformation[,"R"]), decreasing=TRUE,
index.return=TRUE)
motifsInformation <- motifsInformation[idx$ix, ]
#---set
object <- .mbr.set(name="motifsInformation",
para=motifsInformation, object=object)
object <- .mbr.set(name="dualRegulons",
para=rownames(motifsInformation), object=object)
if(!is.null(supplementary.table))
{
##---checks
if(missing(evidenceColname))
stop("'evidenceColname' should be a character value present in
colnames of supplementary.table!")
mbr.checks(name="supplementary.table", para=supplementary.table)
mbr.checks(name="uniqueInput", para=supplementary.table)
mbr.checks(name="evidenceColname", para=evidenceColname)
##---consistency
if(verbose)
cat("-Checking the 'supplementary.table' consistency...\n")
supplementary.table <- .consisSuppTable(object,
supplementary.table,
evidenceColname,
verbose=verbose)
##---find duals
object <- .checkLoops(object, supplementary.table,
evidenceColname, verbose=verbose)
}
return(object)
}
)
#' A preprocessing function for objects of class MBR.
#'
#' This function merges two TNI class objects and creates one MBR class object.
#'
#' @param tni1 A 'TNI' class object.
#' @param tni2 Another 'TNI' class object
#' @param verbose A single logical value specifying to display detailed messages
#' (when verbose=TRUE) or not (when verbose=FALSE).
#' @return An \linkS4class{MBR} object.
#' @examples
#' data("dt4rtn", package = "RTN")
#' gexp <- dt4rtn$gexp
#' annot <- dt4rtn$gexpIDs
#' tfs1 <- dt4rtn$tfs[c("IRF8","IRF1","PRDM1","AFF3","E2F3")]
#' tfs2 <- dt4rtn$tfs[c("HCLS1","STAT4","STAT1","LMO4","ZNF552")]
#' ##---mbrPreprocess
#' rmbr <- mbrPreprocess(gexp=gexp, regulatoryElements1 = tfs1,
#' regulatoryElements2=tfs2, gexpIDs=annot)
#' ##---mbrPermutation
#' rmbr <- mbrPermutation(rmbr, nPermutations=10)
#' ##---mbrBootstrap
#' rmbr <- mbrBootstrap(rmbr, nBootstrap=10)
#' rmbr <- mbrDpiFilter(rmbr)
#' ##---tni2mbrPreprocess
#' tni1 <- mbrGet(rmbr, what="TNI1")
#' tni2 <- mbrGet(rmbr, what="TNI2")
#' rmbr <- tni2mbrPreprocess(tni1, tni2)
#'
#' @import methods
#' @docType methods
#' @rdname tni2mbrPreprocess-methods
#' @aliases tni2mbrPreprocess
#' @export
##------------------------------------------------------------------------------
##Combine two TNIs produced separately
setMethod("tni2mbrPreprocess",
"TNI",
function (tni1, tni2, verbose=TRUE)
{
if(missing(tni1)) stop("NOTE: 'tni1' is missing ", call.=FALSE)
if(missing(tni2)) stop("NOTE: 'tni2' is missing ", call.=FALSE)
mbr.checks (name='tni', para=tni1)
mbr.checks (name='tni', para=tni2)
.combineTNIs (tni1=tni1, tni2=tni2, verbose=verbose)
#---get
gexp <- tni.get(tni1, what="gexp")
regulatoryElements1 <- tni.get(tni1, what="tfs")
regulatoryElements2 <- tni.get(tni2, what="tfs")
##---- creates MBR object
object <- .MBRmaker(class="MBR", gexp=gexp,
regulatoryElements1=regulatoryElements1,
regulatoryElements2=regulatoryElements2)
#---TNIs Update
object <- .mbr.set(name="TNI1", para=tni1, object=object)
object <- .mbr.set(name="TNI2", para=tni2, object=object)
#---statu update
tni_status <- tni.get(tni1, what="status")
status <- names(tni_status[tni_status=="[x]"])
object <- .mbr.set(name="statusUpdate", para=status, object=object)
#---get Updates
tni1_summary <- tni.get(tni1, what="summary")
tni2_summary <- tni.get(tni2, what="summary")
mbr_summary <- mbrGet(object, what="summary")
mbr_para <- mbrGet(object, what="para")
##---permutation
mbr_para$TNIs$perm <- tni1_summary$para$perm
mbr_summary$TNIs$TNI1 <- tni1_summary$results$tnet
colnames(mbr_summary$TNIs$TNI1) <- c('RE', 'Targets', 'Edges')
mbr_summary$TNIs$TNI2 <- tni2_summary$results$tnet
colnames(mbr_summary$TNIs$TNI2) <- c('RE', 'Targets', 'Edges')
##---bootstrap
mbr_para$TNIs$boot <- tni1_summary$para$boot
mbr_summary$TNIs$TNI1 <- tni1_summary$results$tnet
colnames(mbr_summary$TNIs$TNI1) <- c('RE', 'Targets', 'Edges')
mbr_summary$TNIs$TNI2 <- tni2_summary$results$tnet
colnames(mbr_summary$TNIs$TNI2) <- c('RE', 'Targets', 'Edges')
##---summary dpi.filter
mbr_para$TNIs$dpi <- tni1_summary$para$dpi
mbr_summary$TNIs$TNI1 <- tni1_summary$results$tnet
colnames(mbr_summary$TNIs$TNI1) <- c('RE', 'Targets', 'Edges')
mbr_summary$TNIs$TNI2 <- tni2_summary$results$tnet
colnames(mbr_summary$TNIs$TNI2) <- c('RE', 'Targets', 'Edges')
#---set
object <- .mbr.set(name="para", para=mbr_para, object=object)
object <- .mbr.set(name="summary", para=mbr_summary, object=object)
return (object)
}
)
##------------------------------------------------------------------------------
##show summary information on screen
setMethod( "show",
"MBR",
function(object)
{
cat("an MBR (Motifs Between Regulons) object:\n")
message("--status:")
print(object@status, quote=FALSE)
}
)
#' Get information from individual slots in MBR object.
#'
#' Get information from individual slots in an MBR object and any available
#' results from previous analysis.
#'
#' @param object A preprocessed object of class \linkS4class{MBR}
#' @param what a single character value specifying which information should be
#' retrieved from the slots. Options: "TNI1", "TNI2", "testedElementsTNI1",
#' "testedElementsTNI2", "dualRegulons", "results", "para", "summary",
#' "status", "motifsInformation" and "hyperResults"
#' @return A slot content from a object of class 'MBR' \linkS4class{MBR} object
#' @examples
#' data("dt4rtn", package = "RTN")
#' gexp <- dt4rtn$gexp
#' annot <- dt4rtn$gexpIDs
#' tfs1 <- dt4rtn$tfs[c("IRF8","IRF1","PRDM1","AFF3","E2F3")]
#' tfs2 <- dt4rtn$tfs[c("HCLS1","STAT4","STAT1","LMO4","ZNF552")]
#' ##---mbrPreprocess
#' rmbr <- mbrPreprocess(gexp=gexp, regulatoryElements1 = tfs1,
#' regulatoryElements2=tfs2, gexpIDs=annot)
#' ##---get the 'TNI1' slot using 'mbrGet'
#' tni1 <- mbrGet(rmbr, what="TNI1")
#'
#' @import methods
#' @docType methods
#' @rdname mbrGet-methods
#' @aliases mbrGet
#' @export
##------------------------------------------------------------------------------
##get slots from MBR object
setMethod( "mbrGet",
"MBR",
function(object, what="status")
{
##---check input arguments
mbr.checks(name="object", para=object)
mbr.checks(name="mbrGet", para=what)
##---Association options any change needs update!
optsAssoci <- c("testedElementsTNI1", "testedElementsTNI2",
"dualRegulons", "motifsInformation", "results",
"hyperResults")
##---get query
if(what=="TNI1")
{
query <- object@TNI1
}
else if(what=="TNI2")
{
query <- object@TNI2
}
else if(what=="para")
{
query <- object@para
}
else if(what=="summary")
{
query <- object@summary
}
else if(what=="status")
{
query <- object@status
}
else if(what%in%optsAssoci)
{
if(object@status["Association"] != "[x]")
{
warning("NOTE: input 'object' needs 'mbrAssociation'
evaluation!")
query <- NULL
} else {
if(what=="testedElementsTNI1")
{
query <- object@testedElementsTNI1
}
else if(what=="testedElementsTNI2")
{
query <- object@testedElementsTNI2
}
else if(what=="dualRegulons")
{
query <- object@dualRegulons
}
else if(what=="results")
{
query <- object@results
}
else if(what=="motifsInformation")
{
query <- object@results$motifsInformation
}
else if(what=="hyperResults")
{
query <- object@results$hypergeometricResults
}
}
}
return(query)
}
)
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