Step-class: Methods for Step objects

In wzthu/pipeFrame: Pipeline framework for bioinformatics in R

Description

Users can call Step object operation methods below to obtain information in objects.

Usage

## S4 method for signature 'Step'
init(.Object, prevSteps = list(), ...)

## S4 method for signature 'Step'
stepName(.Object, ...)

## S4 method for signature 'Step'
stepType(.Object, attachedTypes = TRUE, ...)

## S4 method for signature 'Step'
pipeName(.Object, ...)

## S4 method for signature 'Step'
input(.Object)

## S4 replacement method for signature 'Step'
input(.Object) <- value

## S4 method for signature 'Step'
output(.Object)

## S4 replacement method for signature 'Step'
output(.Object) <- value

## S4 method for signature 'Step'
param(.Object)

## S4 replacement method for signature 'Step'
param(.Object) <- value

## S4 method for signature 'Step'
property(.Object, ..., pipeName = NULL)

## S4 replacement method for signature 'Step'
property(.Object, pipeName = NULL) <- value

## S4 method for signature 'Step'
report(.Object)

## S4 replacement method for signature 'Step'
report(.Object) <- value

## S4 method for signature 'Step'
argv(.Object)

## S4 method for signature 'Step'
x$name

## S4 replacement method for signature 'Step'
x$name <- value

## S4 method for signature 'Step'
getParam(.Object, item, type = c("input", "output", "other"), ...)

## S4 method for signature 'Step'
getParamItems(.Object, type = c("input", "output", "other"), ...)

## S4 method for signature 'Step'
isReady(.Object, ...)

## S4 method for signature 'Step'
clearStepCache(.Object, ...)

## S4 method for signature 'Step'
getAutoPath(.Object, originPath, regexSuffixName, suffix, ...)

## S4 method for signature 'Step'
checkRequireParam(.Object, ...)

## S4 method for signature 'Step'
checkAllPath(.Object, ...)

## S4 method for signature 'Step'
getParamMD5Path(.Object, ...)

## S4 method for signature 'Step'
getStepWorkDir(.Object, filename = NULL, ...)

## S4 method for signature 'Step'
stepID(.Object, ...)

## S4 method for signature 'Step'
writeLog(
  .Object,
  msg,
  ...,
  isWarnning = FALSE,
  appendLog = TRUE,
  showMsg = TRUE
)

processing(.Object, ...)

genReport(.Object, ...)

Arguments

.Object	Step object scalar. Step object is returned by functions in each step.
prevSteps	List list of Step objects
...	Additional arguments, currently unused.
attachedTypes	Logical scalar. Show the new type name or show the original type name Default: TRUE
value	any type scalar. The value to be set for corresponding item in a list.
pipeName	Character scalar. The pipeline name that this step belongs to. Default: NULL. It will be replace by the only pipeline name.
x	Step object scalar. Step object is returned by functions in each step.
name	Character scalar. Name can be one of inputList, outputList, paramList, allList, propList or the item names of inputList, outputList or paramList
item	Character scalar. The items in parameter list (input, output and other) or report list.
type	Character scalar. Valid types of parameters including "input", "output" and "other"
originPath	Character scalar. The file name for output file is based on this original path name.
regexSuffixName	Character scalar. The suffix for replacement.
suffix	Character scalar. The new suffix for the file.
filename	Character scaler. The name of file under step working directiory
msg	Character scalar. The message to write into log file.
isWarnning	Logical scalar. Set this message as warning message. Default: FALSE
appendLog	Logical scalar. Append to the log file. Default: TRUE
showMsg	Logical scalar. Show the message on screen. Default: TRUE

Details

Step is a S4 class for generating Step S4 objects. All Step objects generated by child classes inherit from Step. To generate new Step objects, a function wrapper with fixed arguments needs to be implemented. Users use this function to generate new Step functions rather than Step S4 class to generate objects.

Value

the function and result of functions:

init	(For package developer only) A Step child class object with initialized input, output and other parameters
stepName	get Step object Character name
stepType	get Step object Character type name (class name)
pipeName	get Step object pipe name
input	get input list
input<-	set input list
output	get output list
output<-	set output list
param	get other parameters list
param<-	set other parameters list
property	get property list
property<-	set property list
report	get report list
report<-	set report list
argv	get arguments list
$	get inputList, outputList, paramList, allList, propList or any item value in inputList, outputList or paramList
$<-	set inputList, outputList, paramList, allList, propList or any item value in inputList, outputList or paramList
getParam	Get parameter value set by process function. See getParamItems to obtain valid items for query.
getParamItems	Get parameter name list
isReady	Is the process ready for downstream process
clearStepCache	Clear cache of Step object
getAutoPath	(For package developer) Developer can use this method to generate new file name based on exist input file name
checkRequireParam	(For package developer) Check required inputs or parameters are filled.
checkRequireParam	(For package developer) Check required inputs are filled.
getParamMD5Path	The Step object storage directory
getStepWorkDir	Get the step work directory of this object
stepID	Get the step ID
writeLog	(For package developer) write log.
processing	(For package developer) Run pipeline step
genReport	(For package developer) Generate report list

Author(s)

Zheng Wei

See Also

setGenome setThreads

Examples

library(BSgenome)
library(rtracklayer)
library(magrittr)

# generate new Step : RandomRegionOnGenome
setClass(Class = "RandomRegionOnGenome",
         contains = "Step"
)

setMethod(
    f = "init",
    signature = "RandomRegionOnGenome",
    definition = function(.Object,prevSteps = list(),...){
        # All arguments in function randomRegionOnGenome
        # will be passed from "..."
        # so get the arguments from "..." first.
        allparam <- list(...)
        sampleNumb <- allparam[["sampleNumb"]]
        regionLen <- allparam[["regionLen"]]
        genome <- allparam[["genome"]]
        outputBed <- allparam[["outputBed"]]
        # no previous steps for this step so ingnore the "prevSteps"
        # begin to set input parameters
        # no input for this step
        # begin to set output parameters
        if(is.null(outputBed)){
            output(.Object)$outputBed <-
                getStepWorkDir(.Object,"random.bed")
        }else{
            output(.Object)$outputBed <- outputBed
        }
        # begin to set other parameters
        param(.Object)$regionLen <-  regionLen
        param(.Object)$sampleNumb <- sampleNumb
        if(is.null(genome)){
            param(.Object)$bsgenome <-  getBSgenome(getGenome())
        }else{
            param(.Object)$bsgenome <-  getBSgenome(genome)
        }
        # don't forget to return .Object
        .Object
    }
)

setMethod(
    f = "processing",
    signature = "RandomRegionOnGenome",
    definition = function(.Object,...){
        # All arguments are set in .Object
        # so we can get them from .Object
        allparam <- list(...)
        sampleNumb <- getParam(.Object,"sampleNumb")
        regionLen <- getParam(.Object,"regionLen")
        bsgenome <- getParam(.Object,"bsgenome")
        outputBed <- getParam(.Object,"outputBed")
        # begin the calculation
        chrlens <-seqlengths(bsgenome)
        selchr <- grep("_|M",names(chrlens),invert=TRUE)
        chrlens <- chrlens[selchr]
        startchrlens <- chrlens - regionLen
        spchrs <- sample(x = names(startchrlens),
        size =  sampleNumb, replace = TRUE,
        prob = startchrlens / sum(startchrlens))
        gr <- GRanges()
        for(chr in names(startchrlens)){
            startpt <- sample(x = 1:startchrlens[chr],
            size = sum(spchrs == chr),replace = FALSE)
            gr <- c(gr,GRanges(seqnames = chr,
            ranges = IRanges(start = startpt, width = 1000)))
        }
        result <- sort(gr,ignore.strand=TRUE)
        rtracklayer::export.bed(object = result, con =  outputBed)
        # don't forget to return .Object
        .Object
    }
)



setMethod(
    f = "genReport",
    signature = "RandomRegionOnGenome",
    definition = function(.Object, ...){
        .Object
    }
)






# This function is exported in NAMESPACE for user to use
randomRegionOnGenome <- function(sampleNumb, regionLen = 1000,
                                 genome = NULL, outputBed = NULL, ...){
    allpara <- c(list(Class = "RandomRegionOnGenome", prevSteps = list()),
                 as.list(environment()),list(...))
    step <- do.call(new,allpara)
    invisible(step)
}


# generate another new Step : OverlappedRandomRegion
setClass(Class = "OverlappedRandomRegion",
         contains = "Step"
)

setMethod(
    f = "init",
    signature = "OverlappedRandomRegion",
    definition = function(.Object,prevSteps = list(),...){
        # All arguments in function overlappedRandomRegion and
        # runOerlappedRandomRegion will be passed from "..."
        # so get the arguments from "..." first.
        allparam <- list(...)
        inputBed <- allparam[["inputBed"]]
        randomBed <- allparam[["randomBed"]]
        outputBed <- allparam[["outputBed"]]
        # inputBed can obtain from previous step object when running
        # runOerlappedRandomRegion
        if(length(prevSteps)>0){
            prevStep <- prevSteps[[1]]
            input(.Object)$randomBed <-  getParam(prevStep,"outputBed")
        }
        # begin to set input parameters
        if(!is.null(inputBed)){
            input(.Object)$inputBed <- inputBed
        }
        if(!is.null(randomBed)){
            input(.Object)$randomBed <- randomBed
        }
        # begin to set output parameters
        # the output is recemended to set under the step work directory
        if(!is.null(outputBed)){
            output(.Object)$outputBed <-  outputBed
        }else{
            output(.Object)$outputBed <-
                getAutoPath(.Object, getParam(.Object, "inputBed"),
                            "bed", suffix = "bed")
            # the path can also be generate in this way
            # ib <- getParam(.Object,"inputBed")
            # output(.Object)$outputBed <-
            #    file.path(getStepWorkDir(.Object),
            #    paste0(substring(ib,1,nchar(ib)-3), "bed"))
        }
        # begin to set other parameters
        # no other parameters
        # don't forget to return .Object


        .Object
    }
)
setMethod(
    f = "processing",
    signature = "OverlappedRandomRegion",
    definition = function(.Object,...){
        # All arguments are set in .Object
        # so we can get them from .Object
        allparam <- list(...)
        inputBed <- getParam(.Object,"inputBed")
        randomBed <- getParam(.Object,"randomBed")
        outputBed <- getParam(.Object,"outputBed")

        # begin the calculation
        gr1 <- import.bed(con = inputBed)
        gr2 <- import.bed(con = randomBed)
        gr <- second(findOverlapPairs(gr1,gr2))
        export.bed(gr,con = outputBed)
        # don't forget to return .Object
        .Object
    }
)


setMethod(
    f = "genReport",
    signature = "OverlappedRandomRegion",
    definition = function(.Object, ...){
        .Object
    }
)




# This function is exported in NAMESPACE for user to use
overlappedRandomRegion <- function(inputBed, randomBed,
                                   outputBed = NULL, ...){
    allpara <- c(list(Class = "OverlappedRandomRegion",
        prevSteps = list()),as.list(environment()),list(...))
    step <- do.call(new,allpara)
    invisible(step)
}

setGeneric("runOverlappedRandomRegion",
           function(prevStep,
                    inputBed,
                    randomBed = NULL,
                    outputBed = NULL,
                    ...) standardGeneric("runOverlappedRandomRegion"))



setMethod(
    f = "runOverlappedRandomRegion",
    signature = "Step",
    definition = function(prevStep,
                          inputBed,
                          randomBed = NULL,
                          outputBed = NULL,
                          ...){
        allpara <- c(list(Class = "OverlappedRandomRegion",
            prevSteps = list(prevStep)),as.list(environment()),list(...))
        step <- do.call(new,allpara)
        invisible(step)
    }
)

# add to graph
addEdges(edges = c("RandomRegionOnGenome","OverlappedRandomRegion"),
         argOrder = 1)
# begin to test pipeline
setGenome("hg19")
# generate test BED file
test_bed <- file.path(tempdir(),"test.bed")
library(rtracklayer)
export.bed(GRanges("chr7:1-127473000"),test_bed)


rd <- randomRegionOnGenome(10000)
overlap <- runOverlappedRandomRegion(rd, inputBed = test_bed)

randombed <- getParam(rd,"outputBed")

randombed

overlap1 <-
    overlappedRandomRegion(inputBed = test_bed, randomBed = randombed)

clearStepCache(overlap1)
overlap1 <-
    overlappedRandomRegion(inputBed = test_bed, randomBed = randombed)
clearStepCache(rd)
clearStepCache(overlap1)
rd <- randomRegionOnGenome(10000) %>%
runOverlappedRandomRegion(inputBed = test_bed)

stepName(rd)
stepID(rd)


isReady(rd)

wzthu/pipeFrame documentation built on Sept. 22, 2021, 4:36 p.m.