comparison waveica_wrapper.R @ 2:d08deef1eb44 draft

"planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/waveica commit e33ef984e78721ed37d825c6672795a539a461e1"

1:2bcfd5b450bb

waveica <- function(
    data,
    wavelet_filter,
    wavelet_length,
    k,
    t,
    t2,
    alpha,
    exclude_blanks
) {

    # get input from the Galaxy, preprocess data
    data <- read.csv(data, header = TRUE, row.names = "sampleName")

    # sort data by injection order
    data <- data[order(data$injectionOrder, decreasing = FALSE), ]

    data <- enumerate_groups(data)

    # remove blanks from dataset
    if (exclude_blanks) {
        data <- exclude_group(data)
    }

    # separate data into features, batch and group
    features <- data[, -c(1:4)]
    group <- as.numeric(data$class)
    batch <- data$batch

    # run WaveICA
    normalized_data <- WaveICA::WaveICA(
        data = features,
        wf = get_wf(wavelet_filter, wavelet_length),
        batch = batch,
        group = group,
        K = k,
        t = t,
        t2 = t2,
        alpha = alpha
        )

    return(normalized_data)
}


# Match group labels with [blank/sample/qc] and enumerate them
enumerate_groups <- function(data) {

    data$sampleType[grepl("blank", tolower(data$sampleType))] <- 0
    data$sampleType[grepl("sample", tolower(data$sampleType))] <- 1
    data$sampleType[grepl("qc", tolower(data$sampleType))] <- 2

    return(data)
}


# Create appropriate input for R wavelets function
get_wf <- function(wavelet_filter, wavelet_length) {
    wf <- paste(wavelet_filter, wavelet_length, sep = "")

    # exception to the wavelet function
    if (wf == "d2") {
        wf <- "haar"
        }

    return(wf)
}


# Exclude blanks from a dataframe
exclude_group <- function(data) {
    row_idx_to_exclude <- which(data$class %in% 0)
    if (length(row_idx_to_exclude) > 0) {
        data_without_blanks <- data[-c(row_idx_to_exclude), ]
        msg <- paste("Blank samples have been excluded from the dataframe.\n")
        cat(msg)
        return(data_without_blanks)
        }
    else {
        return(data)
    }
}


# Store output of WaveICA in a tsv file
store_data <- function(normalized_data, output) {
    write.table(normalized_data, file = output, sep = "\t", col.names = NA)
    cat("Normalization has been completed.\n")
}

2:d08deef1eb44

waveica <- function(data,
                    wavelet_filter,
                    wavelet_length,
                    k,
                    t,
                    t2,
                    alpha,
                    exclude_blanks) {

  # get input from the Galaxy, preprocess data
  data <- read.csv(data, header = TRUE)

  required_columns <- c("sampleName", "class", "sampleType", "injectionOrder", "batch")
  if (anyNA(data)) {
    stop("Error: dataframe cannot contain NULL values!
Make sure that your dataframe does not contain empty cells")
  } else if (!all(required_columns %in% colnames(data))) {
    stop("Error: missing metadata!
Make sure that the following columns are present in your dataframe: [sampleName, class, sampleType, injectionOrder, batch]")
  }

  # sort data by injection order
  data <- data[order(data[, "batch"],
    data[, "injectionOrder"],
    decreasing = FALSE
  ), ]

  # separate data into features, batch and group
  feature_columns <- colnames(data)[!colnames(data) %in% required_columns]
  features <- data[, feature_columns]
  group <- enumerate_groups(as.character(data$sampleType))
  batch <- data$batch

  # run WaveICA
  features <- WaveICA::WaveICA(
    data = features,
    wf = get_wf(wavelet_filter, wavelet_length),
    batch = batch,
    group = group,
    K = k,
    t = t,
    t2 = t2,
    alpha = alpha
  )

  data[, feature_columns] <- features$data_wave

  # remove blanks from dataset
  if (exclude_blanks) {
    data <- exclude_group(data, group)
  }

  return(data)
}


# Match group labels with [blank/sample/qc] and enumerate them
enumerate_groups <- function(group) {
  group[grepl("blank", tolower(group))] <- 0
  group[grepl("sample", tolower(group))] <- 1
  group[grepl("qc", tolower(group))] <- 2

  return(group)
}


# Create appropriate input for R wavelets function
get_wf <- function(wavelet_filter, wavelet_length) {
  wf <- paste(wavelet_filter, wavelet_length, sep = "")

  # exception to the wavelet function
  if (wf == "d2") {
    wf <- "haar"
  }

  return(wf)
}


# Exclude blanks from a dataframe
exclude_group <- function(data, group) {
  row_idx_to_exclude <- which(group %in% 0)
  if (length(row_idx_to_exclude) > 0) {
    data_without_blanks <- data[-c(row_idx_to_exclude), ]
    cat("Blank samples have been excluded from the dataframe.\n")
    return(data_without_blanks)
  } else {
    return(data)
  }
}


# Store output of WaveICA in a tsv file
store_data <- function(data, output) {
  write.table(data, file = output, sep = "\t", row.names = FALSE, quote = FALSE)
  cat("Normalization has been completed.\n")
}