comparison w4mclassfilter_wrapper.R @ 12:38f509903a0b draft

"planemo upload for repository https://github.com/HegemanLab/w4mclassfilter_galaxy_wrapper/tree/master commit b9712e554d16ed26f6c6d0c2e8cd74552b49f694"

11:9f5c0e23c205

## libraries
##----------

suppressMessages(library(w4mclassfilter))

if(packageVersion("w4mclassfilter") < "0.98.0")
    stop("Please use 'w4mclassfilter' versions of 0.98.0 and above")

## constants
##----------

modNamC <- "w4mclassfilter" ## module name

variableMetadata_out <- as.character(argVc["variableMetadata_out"])

# other parameters

transformation <- as.character(argVc["transformation"])
wildcards <- as.logical(argVc["wildcards"])
sampleclassNames <- as.character(argVc["sampleclassNames"])
sampleclassNames <- strsplit(x = sampleclassNames, split = ",", fixed = TRUE)[[1]]
if (wildcards) {
  sampleclassNames <- gsub("[.]", "[.]", sampleclassNames)

variable_range_filter <- strsplit(x = variable_range_filter, split = ",", fixed = TRUE)[[1]]

## -----------------------------
## Transformation and imputation
## -----------------------------
my_w4m_filter_imputation <- if (transformation == "log10") {
  function(m) {
    if (!is.matrix(m))
      stop("Cannot impute and transform data - the supplied data is not in matrix form")
    if (nrow(m) == 0)
      stop("Cannot impute and transform data - data matrix has no rows")
    if (ncol(m) == 0)
      stop("Cannot impute and transform data - data matrix has no columns")
    suppressWarnings(
      # suppress warnings here since non-positive values will produce NaN's that will be fixed in the next step
      m <- log10(m)
    )
    return ( w4m_filter_imputation(m) )
  }
} else if (transformation == "log2") {
  function(m) {
    if (!is.matrix(m))
      stop("Cannot impute and transform data - the supplied data is not in matrix form")
    if (nrow(m) == 0)
      stop("Cannot impute and transform data - data matrix has no rows")
    if (ncol(m) == 0)
      stop("Cannot impute and transform data - data matrix has no columns")
    suppressWarnings(
      # suppress warnings here since non-positive values will produce NaN's that will be fixed in the next step
      m <- log2(m)
    )
    return ( w4m_filter_imputation(m) )
  }
} else {
  # use the method from the w4mclassfilter class
  w4m_filter_imputation
}

##------------------------------
## Computation
##------------------------------

, include               = inclusive
, class_column          = classnameColumn
, samplename_column     = samplenameColumn
, variable_range_filter = variable_range_filter
, failure_action        = my_print
, data_imputation       = my_w4m_filter_imputation
)

my_print("\nResult of '", modNamC, "' Galaxy module call to 'w4mclassfilter::w4m_filter_by_sample_class' R function: ",
    as.character(result), "\n", sep = "")

12:38f509903a0b

## libraries
##----------

suppressMessages(library(w4mclassfilter))

if(packageVersion("w4mclassfilter") < "0.98.12")
    stop("Please use 'w4mclassfilter' versions of 0.98.12 and above")

## constants
##----------

modNamC <- "w4mclassfilter" ## module name

variableMetadata_out <- as.character(argVc["variableMetadata_out"])

# other parameters

transformation <- as.character(argVc["transformation"])
my_imputation_label <- as.character(argVc["imputation"])
my_imputation_function <- if (my_imputation_label == "zero") {
  w4m_filter_zero_imputation
} else if (my_imputation_label == "center") {
  w4m_filter_median_imputation
} else if (my_imputation_label == "none") {
  w4m_filter_no_imputation
} else {
  stop(sprintf("Unknown value %s supplied for 'imputation' parameter.  Expected one of {zero,center,none}."))
}
wildcards <- as.logical(argVc["wildcards"])
sampleclassNames <- as.character(argVc["sampleclassNames"])
sampleclassNames <- strsplit(x = sampleclassNames, split = ",", fixed = TRUE)[[1]]
if (wildcards) {
  sampleclassNames <- gsub("[.]", "[.]", sampleclassNames)

variable_range_filter <- strsplit(x = variable_range_filter, split = ",", fixed = TRUE)[[1]]

## -----------------------------
## Transformation and imputation
## -----------------------------
my_transformation_and_imputation <- if (transformation == "log10") {
  function(m) {
    if (!is.matrix(m))
      stop("Cannot transform and impute data - the supplied data is not in matrix form")
    if (nrow(m) == 0)
      stop("Cannot transform and impute data - data matrix has no rows")
    if (ncol(m) == 0)
      stop("Cannot transform and impute data - data matrix has no columns")
    suppressWarnings({
      # suppress warnings here since non-positive values will produce NaN's that will be fixed in the next step
      m <- log10(m)
      m[is.na(m)] <- NA
    })
    return ( my_imputation_function(m) )
  }
} else if (transformation == "log2") {
  function(m) {
    if (!is.matrix(m))
      stop("Cannot transform and impute data - the supplied data is not in matrix form")
    if (nrow(m) == 0)
      stop("Cannot transform and impute data - data matrix has no rows")
    if (ncol(m) == 0)
      stop("Cannot transform and impute data - data matrix has no columns")
    suppressWarnings({
      # suppress warnings here since non-positive values will produce NaN's that will be fixed in the next step
      m <- log2(m)
      m[is.na(m)] <- NA
    })
    return ( my_imputation_function(m) )
  }
} else {
  # use the method from the w4mclassfilter class
  my_imputation_function
}

##------------------------------
## Computation
##------------------------------

, include               = inclusive
, class_column          = classnameColumn
, samplename_column     = samplenameColumn
, variable_range_filter = variable_range_filter
, failure_action        = my_print
, data_imputation       = my_transformation_and_imputation
)

my_print("\nResult of '", modNamC, "' Galaxy module call to 'w4mclassfilter::w4m_filter_by_sample_class' R function: ",
    as.character(result), "\n", sep = "")