R/BasePositionNormalization.R

In aroma.affymetrix: Analysis of Large Affymetrix Microarray Data Sets

###########################################################################/**
# @RdocClass BasePositionNormalization
#
# @title "The BasePositionNormalization class"
#
# \description{
#  @classhierarchy
#
#  This class represents a normalization method that corrects for systematic
#  effects in the probe intensities due to differences in positioning of
#  A, C, G, and T:s in the probe sequences.
# }
#
# @synopsis
#
# \arguments{
#   \item{...}{Arguments passed to the constructor of
#     @see "LinearModelProbeSequenceNormalization".}
#   \item{model}{A @character string specifying the model used to fit
#     the base-count effects.}
#   \item{df}{The degrees of freedom of the model.}
# }
#
# \section{Fields and Methods}{
#  @allmethods "public"
# }
#
# @author "HB, MR"
#*/###########################################################################
setConstructorS3("BasePositionNormalization", function(..., model=c("smooth.spline"), df=5) {
  # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
  # Validate arguments
  # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
  # Argument 'model':
  model <- match.arg(model)

  # Argument 'df':
  df <- Arguments$getInteger(df, range=c(1,1e3))

  extend(LinearModelProbeSequenceNormalization(...), "BasePositionNormalization",
    .model = model,
    .df = df
  )
})


setMethodS3("getAsteriskTags", "BasePositionNormalization", function(this, collapse=NULL, ...) {
  tags <- NextMethod("getAsteriskTags", collapse=NULL)

  # Add model tag?
  model <- this$.model
  if (model != "smooth.spline") {
    tags <- c(tags, model)
  }

  # Add df tag?
  df <- this$.df
  if (df != 5) {
    tags <- c(tags, sprintf("df=%d", df))
  }

  # Collapse?
  tags <- paste(tags, collapse=collapse)

  tags
}, protected=TRUE)



setMethodS3("getParameters", "BasePositionNormalization", function(this, ...) {
  # Get parameters from super class
  params <- NextMethod("getParameters")

  params <- c(params, list(
    model = this$.model,
    df = this$.df
  ))

  params
}, protected=TRUE)



setMethodS3("getDesignMatrix", "BasePositionNormalization", function(this, cells=NULL, ..., force=FALSE, cache=TRUE, verbose=FALSE) {
  # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
  # Validate arguments
  # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
  # Argument 'cells':
  if (is.null(cells)) {
  } else {
    # Validated below...
  }

  # Argument 'verbose':
  verbose <- Arguments$getVerbose(verbose)
  if (verbose) {
    pushState(verbose)
    on.exit(popState(verbose))
  }

  verbose && enter(verbose, "Retrieving design matrix")
  verbose && cat(verbose, "Cells:")
  verbose && str(verbose, cells)

  verbose && enter(verbose, "Getting algorithm parameters")
  params <- getParameters(this, expand=FALSE, verbose=less(verbose, 1))
  model <- params$model
  df <- params$df
  verbose && cat(verbose, "Model: ", model)
  verbose && cat(verbose, "Degrees of freedom: ", df)
  verbose && exit(verbose)

  # Locate AromaCellSequenceFile holding probe sequences
  acs <- getAromaCellSequenceFile(this, verbose=less(verbose, 5))


  # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
  # Check file cache
  # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
  key <- list(
    method="getDesignMatrix", class=class(this[1]),
    cells=cells,
    model=model, df=df,
    acs=list(fullname=getFullName(acs))
  )

  dirs <- c("aroma.affymetrix", getChipType(acs))
  if (!force) {
    X <- loadCache(key=key, dirs=dirs)
    if (!is.null(X)) {
      verbose && cat(verbose, "Cached results found.")
      verbose && exit(verbose)
      return(X)
    }
  }

  verbose && enter(verbose, "Reading probe sequences")
  seqs <- readSequenceMatrix(acs, cells=cells, what="raw",
                                                verbose=less(verbose, 5))
  # Not needed anymore
  acs <- NULL
  verbose && cat(verbose, "Probe-sequence matrix:")
  verbose && str(verbose, seqs)
  verbose && exit(verbose)

  verbose && enter(verbose, "Building probe-position design matrix")
  verbose && cat(verbose, "Degrees of freedom: ", df)
  X <- getProbePositionEffectDesignMatrix(seqs, df=df,
                                               verbose=less(verbose, 5))
  # Not needed anymore
  seqs <- NULL

  # Garbage collect
  gc <- gc()
  verbose && print(verbose, gc)

  verbose && cat(verbose, "Design matrix:")
  verbose && str(verbose, X)
  verbose && cat(verbose, "RAM: %s", hsize(object.size(X), digits = 2L, standard = "IEC"))
  verbose && exit(verbose)

  # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
  # Cache results?
  # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
  if (cache) {
    saveCache(X, key=key, dirs=dirs)
  }

  verbose && exit(verbose)

  X
}, private=TRUE)



setMethodS3("getSignalTransform", "BasePositionNormalization", function(this, ...) {
  params <- getParameters(this, expand=FALSE, ...)
  shift <- params$shift
  # Not needed anymore
  params <- NULL

  transform <- function(y, ...) {
    y <- y + shift
    y <- log2(y)
    y
  }

  transform
}, protected=TRUE)