view dimsPredictPuritySingle.R @ 9:da36e8bbcfbd draft

planemo upload for repository https://github.com/computational-metabolomics/mspurity-galaxy commit 20a48a1862267264f98b7c514287f9a5cba1143f
author computational-metabolomics
date Thu, 13 Jun 2024 11:35:07 +0000
parents a0ee43397d1e
children
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library(msPurity)
library(optparse)
print(sessionInfo())

option_list <- list(
    make_option(c("--mzML_file"), type = "character"),
    make_option(c("--mzML_files"), type = "character"),
    make_option(c("--mzML_filename"), type = "character", default = ""),
    make_option(c("--mzML_galaxy_names"), type = "character", default = ""),
    make_option(c("--peaks_file"), type = "character"),
    make_option(c("-o", "--out_dir"), type = "character"),
    make_option("--minoffset", default = 0.5),
    make_option("--maxoffset", default = 0.5),
    make_option("--ilim", default = 0.05),
    make_option("--ppm", default = 4),
    make_option("--dimspy", action = "store_true"),
    make_option("--sim", action = "store_true"),
    make_option("--remove_nas", action = "store_true"),
    make_option("--iwNorm", default = "none", type = "character"),
    make_option("--file_num_dimspy", default = 1),
    make_option("--exclude_isotopes", action = "store_true"),
    make_option("--isotope_matrix", type = "character")
)

# store options
opt <- parse_args(OptionParser(option_list = option_list))

print(sessionInfo())
print(opt)

print(opt$mzML_files)
print(opt$mzML_galaxy_names)

str_to_vec <- function(x) {
    print(x)
    x <- trimws(strsplit(x, ",")[[1]])
    return(x[x != ""])
}

find_mzml_file <- function(mzML_files, galaxy_names, mzML_filename) {
    mzML_filename <- trimws(mzML_filename)
    mzML_files <- str_to_vec(mzML_files)
    galaxy_names <- str_to_vec(galaxy_names)
    if (mzML_filename %in% galaxy_names) {
        return(mzML_files[galaxy_names == mzML_filename])
    } else {
        stop(paste("mzML file not found - ", mzML_filename))
    }
}


if (is.null(opt$dimspy)) {
    df <- read.table(opt$peaks_file, header = TRUE, sep = "\t")
    if (file.exists(opt$mzML_file)) {
        mzML_file <- opt$mzML_file
    } else if (!is.null(opt$mzML_files)) {
        mzML_file <- find_mzml_file(
            opt$mzML_files, opt$mzML_galaxy_names,
            opt$mzML_filename
        )
    } else {
        mzML_file <- file.path(opt$mzML_file, filename)
    }
} else {
    indf <- read.table(opt$peaks_file,
        header = TRUE, sep = "\t", stringsAsFactors = FALSE
    )

    filename <- colnames(indf)[8:ncol(indf)][opt$file_num_dimspy]
    print(filename)
    # check if the data file is mzML or RAW (can only use mzML currently) so
    # we expect an mzML file of the same name in the same folder
    indf$i <- indf[, colnames(indf) == filename]
    indf[, colnames(indf) == filename] <- as.numeric(indf[, colnames(indf) == filename])

    filename <- sub("raw", "mzML", filename, ignore.case = TRUE)
    print(filename)

    if (file.exists(opt$mzML_file)) {
        mzML_file <- opt$mzML_file
    } else if (!is.null(opt$mzML_files)) {
        mzML_file <- find_mzml_file(opt$mzML_files, opt$mzML_galaxy_names, filename)
    } else {
        mzML_file <- file.path(opt$mzML_file, filename)
    }

    # Update the dimspy output with the correct information
    df <- indf[4:nrow(indf), ]
    if ("blank_flag" %in% colnames(df)) {
        df <- df[df$blank_flag == 1, ]
    }
    colnames(df)[colnames(df) == "m.z"] <- "mz"

    if ("nan" %in% df$mz) {
        df[df$mz == "nan", ]$mz <- NA
    }
    df$mz <- as.numeric(df$mz)
}

if (!is.null(opt$remove_nas)) {
    df <- df[!is.na(df$mz), ]
}

if (is.null(opt$isotope_matrix)) {
    im <- NULL
} else {
    im <- read.table(opt$isotope_matrix,
        header = TRUE, sep = "\t", stringsAsFactors = FALSE
    )
}

if (is.null(opt$exclude_isotopes)) {
    isotopes <- FALSE
} else {
    isotopes <- TRUE
}

if (is.null(opt$sim)) {
    sim <- FALSE
} else {
    sim <- TRUE
}

minOffset <- as.numeric(opt$minoffset)
maxOffset <- as.numeric(opt$maxoffset)

if (opt$iwNorm == "none") {
    iwNorm <- FALSE
    iwNormFun <- NULL
} else if (opt$iwNorm == "gauss") {
    iwNorm <- TRUE
    iwNormFun <- msPurity::iwNormGauss(minOff = -minOffset, maxOff = maxOffset)
} else if (opt$iwNorm == "rcosine") {
    iwNorm <- TRUE
    iwNormFun <- msPurity::iwNormRcosine(minOff = -minOffset, maxOff = maxOffset)
} else if (opt$iwNorm == "QE5") {
    iwNorm <- TRUE
    iwNormFun <- msPurity::iwNormQE.5()
}

print("FIRST ROWS OF PEAK FILE")
print(head(df))
print(mzML_file)
predicted <- msPurity::dimsPredictPuritySingle(df$mz,
    filepth = mzML_file,
    minOffset = minOffset,
    maxOffset = maxOffset,
    ppm = opt$ppm,
    mzML = TRUE,
    sim = sim,
    ilim = opt$ilim,
    isotopes = isotopes,
    im = im,
    iwNorm = iwNorm,
    iwNormFun = iwNormFun
)
predicted <- cbind(df, predicted)

print(head(predicted))
print(file.path(opt$out_dir, "dimsPredictPuritySingle_output.tsv"))

write.table(predicted,
    file.path(opt$out_dir, "dimsPredictPuritySingle_output.tsv"),
    row.names = FALSE, sep = "\t"
)