R/AllClasses.R

In RTN: RTN: Reconstruction of Transcriptional regulatory Networks and analysis of regulons

##Class TNI (Transcriptional Network Inference)
setClass(
  "TNI",
  representation(
    gexp="matrix",
    regulatoryElements="character",
    targetElements="character",
    modulators="char_Or_null",
    rowAnnotation="data.frame",
    colAnnotation="data.frame",
    para="list",
    results="list",
    summary="list",
    status="character"
  ),
  prototype=list(
    gexp=matrix(),
    regulatoryElements=character(),
    targetElements=character(),
    modulators=character(),
    rowAnnotation=data.frame(),
    colAnnotation=data.frame(),
    para=list(),
    results=list(),
    summary=list(),
    status=character()
  )
)

##Class TNA (Transcriptional Network Analysis)
setClass(
  "TNA",
  representation(
    referenceNetwork="matrix",
    transcriptionalNetwork="matrix",
    regulatoryElements="character",
    phenotype="num_Or_int_Or_null", 
    hits="char_Or_null",
    gexp="matrix",
    rowAnnotation="data.frame",
    colAnnotation="data.frame",
    listOfReferenceRegulons="list",
    listOfRegulons="list",
    listOfModulators="list",
    para="list",
    results="list",
    summary="list",
    status="list"
  ),
  prototype=list(
    referenceNetwork=matrix(),
    transcriptionalNetwork=matrix(),
    regulatoryElements=character(),
    phenotype=numeric(),
    hits=character(),
    gexp=matrix(),
    rowAnnotation=data.frame(),
    colAnnotation=data.frame(),
    listOfReferenceRegulons=list(),
    listOfRegulons=list(),
    listOfModulators=list(),
    para=list(),
    results=list(),
    summary=list(),
    status=list()
  )
)

##Class AVS (Associated Variant Set)
setClass(
  "AVS",
  representation(
    markers="character",
    validatedMarkers="data.frame",
    variantSet="list",
    randomSet="list",
    para="list",
    results="list",
    summary="list",
    status="character"
  ),
  prototype=list(
    markers=character(),
    validatedMarkers=data.frame(),
    variantSet=list(),
    randomSet=list(),
    para=list(),
    results=list(),
    summary=list(),
    status=character()
  )
)