1. MsBackendMassbank
  2. Commit 13a450da428d2c80c2941bda586d9f82c2b55cd0
Browse code

updated functions to be aligned with RforMassSpectrometry

Michael Witting authored on 17/04/2020 08:56:41
Showing 3 changed files
R/MsBackendMassbank.R
History View file @ 13a450d
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+
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+#' @include hidden_aliases.R
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+NULL
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+
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+#' @title MS data backend for mgf files
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+#'
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+#' @aliases MsBackendMassbank-class
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+#'
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+#' @description
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+#'
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+#' The `MsBackendMassbank` class supports import of MS/MS spectra data from
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+#' files in Mascot Generic Format
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+#' ([mgf](http://www.matrixscience.com/help/data_file_help.html))
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+#' files. After initial import, the full MS data is kept in
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+#' memory. `MsBackendMassbank` extends the [MsBackendDataFrame()] backend
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+#' directly and supports thus the [applyProcessing()] function to make
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+#' data manipulations persistent. The backend does however not
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+#' support export to mgf files yet.
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+#'
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+#' New objects are created with the `MsBackendMassbank` function. The
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+#' `backendInitialize` method has to be subsequently called to
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+#' initialize the object and import MS/MS data from (one or more) mgf
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+#' files.  Optional parameter `nonStop` allows to specify whether the
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+#' import returns with an error if one of the xml files lacks required
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+#' data, such as `mz` and `intensity` values (default `nonStop =
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+#' FALSE`), or whether only affected file(s) is(are) skipped and a
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+#' warning is shown (`nonStop = TRUE`). Note that any other error
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+#' (such as xml import error) will abort import regardless of
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+#' parameter `nonStop`.
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+#'
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+#' @param object Instance of `MsBackendMassbank` class.
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+#'
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+#' @param files `character` with the (full) file name(s) of the mgf file(s)
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+#'     from which MS/MS data should be imported.
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+#'
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+#' @param nonStop `logical(1)` whether import should be stopped if an
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+#'     xml file does not contain all required fields. Defaults to
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+#'     `nonStop = FALSE`.
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+#'
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+#' @param BPPARAM Parameter object defining the parallel processing
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+#'     setup to import data in parallel. Defaults to `BPPARAM =
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+#'     bpparam()`. See [bpparam()] for more information.
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+#'
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+#' @param ... Currently ignored.
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+#'
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+#' @author Michael Witting
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+#'
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+#' @importClassesFrom Spectra MsBackendDataFrame
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+#'
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+#' @exportClass MsBackendMassbank
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+#'
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+#' @name MsBackendMassbank
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+#'
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+#' @examples
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+#'
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+#' ## Create an MsBackendHmdbXml backend and import data from test xml files.
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+#' fls <- dir(system.file("extdata", package = "MsBackendMassbank"),
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+#'     full.names = TRUE, pattern = "mgf$")
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+#' be <- backendInitialize(MsBackendMassbank(), fls)
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+#' be
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+#'
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+#' be$msLevel
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+#' be$intensity
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+#' be$mz
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+NULL
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+
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+setClass("MsBackendMassbank",
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+         contains = "MsBackendDataFrame",
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+         prototype = prototype(spectraData = DataFrame(),
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+                               readonly = FALSE,
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+                               version = "0.1"))
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+
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+#' @importMethodsFrom Spectra backendInitialize asDataFrame<- $<- $
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+#'
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+#' @importFrom BiocParallel bpparam
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+#'
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+#' @importMethodsFrom BiocParallel bplapply
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+#'
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+#' @importFrom methods validObject
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+#'
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+#' @exportMethod backendInitialize
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+#'
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+#' @rdname MsBackendMassbank
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+setMethod("backendInitialize", signature = "MsBackendMassbank",
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+          function(object, files, nonStop = FALSE, ..., BPPARAM = bpparam()) {
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+            if (missing(files) || !length(files))
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+              stop("Parameter 'files' is mandatory for ", class(object))
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+            if (!is.character(files))
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+              stop("Parameter 'files' is expected to be a character vector",
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+                   " with the files names from where data should be",
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+                   " imported")
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+            files <- normalizePath(files)
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+            if (any(!file.exists(files)))
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+              stop("file(s) ",
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+                   paste(files[!file.exists(files)], collapse = ", "),
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+                   " not found")
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+            ## Import data and rbind.
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+            message("Start data import from ", length(files), " files ... ",
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+                    appendLF = FALSE)
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+            res <- bplapply(files, FUN = .read_massbank,
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+                            nonStop = nonStop, BPPARAM = BPPARAM)
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+            message("done")
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+            res <- do.call(rbind, res)
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+            if (nonStop && length(files) > nrow(res))
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+              warning("Import failed for ", length(files) - nrow(res),
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+                      " files")
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+            asDataFrame(object) <- res
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+            object$dataStorage <- "<memory>"
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+            object$centroided <- TRUE
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+            validObject(object)
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+            object
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+          })
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+
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+#' @rdname MsBackendMassbank
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+#'
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+#' @importFrom methods new
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+#'
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+#' @export MsBackendMassbank
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+MsBackendMassbank <- function() {
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+  new("MsBackendMassbank")
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+}
R/functions-massbank.R
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-# all fields are found here
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-# https://github.com/MassBank/MassBank-web/blob/dev/Documentation/MassBankRecordFormat.md
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-
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-#'
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-#'
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-#'
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-.import_massbank_ms_ms_spectrum <- function(x) {
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-
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-  if (!is.character(x) || length(x) != 1)
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-    stop("'x' has to be of type character with length 1")
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-
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-  con <- file(x)
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-  mb_record <- readLines(con)
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-  close(con)
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-
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-  # isolate spectrum and basic metadata (default)
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-  recordinfo <- .isolate_recordinfo(mb_record)
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-  spectrum <- .isolate_spectrum(mb_record)
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-
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-  # idea: isolate only additional information if requested
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-  if(isolate_ch) {
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-    ch <- .isolate_chemical(mb_record)
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-  } else {
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-    ch <- NULL
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+##' @param f `character(1)` with the path to an MassBank file.
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+##'
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+##' @param msLevel `numeric(1)` with the MS level. Default is 2.
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+##'
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+##' @param ... Additional parameters, currently ignored.
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+##'
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+##' @importFrom S4Vectors DataFrame
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+##'
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+##' @importFrom IRanges NumericList
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+##'
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+##' @author Michael Witting
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+##'
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+##' @noRd
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+.read_massbank <- function(f, msLevel = 2L, ...) {
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+
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+  if (length(f) != 1L)
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+    stop("Please provide a single mgf file.")
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+
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+  mb <- scan(file = f, what = "",
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+              sep = "\n", quote = "",
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+              allowEscapes = FALSE,
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+              quiet = TRUE)
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+
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+  begin <- grep("ACCESSION:", mb) + 1L
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+  end <- grep("//", mb)
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+  n <- length(begin)
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+  sp <- vector("list", length = n)
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+
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+  for (i in seq(along = sp))
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+    sp[[i]] <- .extract_mb_spectrum(mb[begin[i]:end[i]])
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+
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+  res <- DataFrame(do.call(rbind, sp))
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+
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+  for (i in seq_along(res)) {
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+    if (all(lengths(res[[i]]) == 1))
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+      res[[i]] <- unlist(res[[i]])
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   }
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-  # create Spectra object with metadata
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+  res$mz <- IRanges::NumericList(res$mz)
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+  res$intensity <- IRanges::NumericList(res$intensity)
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+  res$dataOrigin <- f
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+  res$msLevel <- as.integer(msLevel)
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+  res
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 }
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-#'
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-#'
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-#'
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-.isolate_spectrum <- function(mb_record) {
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-
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-  #read the spectrum
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-  spectrum_start <- grep("PK$PEAK:", mb_record, fixed = TRUE) + 1
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-  spectrum_end <- tail(grep("//", mb_record, fixed = TRUE), 1) - 1
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-
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-  if(spectrum_start < spectrum_end){
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-    splitted <- strsplit(mb_record[spectrum_start:(spectrum_end)]," ")
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-    spectrum <- matrix(nrow = spectrum_end + 1 - spectrum_start, ncol = 3)
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-    for(k in 1:length(splitted)){
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-      splitted[[k]] <- splitted[[k]][which(splitted[[k]] != "")]
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-      spectrum[k,] <- splitted[[k]]
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-    }
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-    # convert to data frame and adjust data type
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-    spectrum <- as.data.frame(spectrum, stringsAsFactors = FALSE)
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-    spectrum[] <- lapply(spectrum, type.convert)
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-    colnames(spectrum) <- c("m/z", "int", "rel.int.")
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-    # return spectrum
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-    return(spectrum)
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+##' @param mb `character()` of lines defining a spectrum in mgf
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+##'     format.
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+##'
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+##' @author Michael Witting
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+##'
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+##' @noRd
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+.extract_mb_spectrum <- function(mb) {
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-  } else {
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+  #read the spectrum
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+  spectrum_start <- grep("PK$PEAK:", mb, fixed = TRUE) + 1
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+  spectrum_end <- tail(grep("//", mb, fixed = TRUE), 1) - 1
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-    stop("Could not find PK$PEAK or //. Please check the supplied MB record file")
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+  splitted <- strsplit(mb[spectrum_start:(spectrum_end)]," ")
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+  spectrum <- matrix(nrow = spectrum_end + 1 - spectrum_start, ncol = 3)
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+  for(k in 1:length(splitted)){
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+    splitted[[k]] <- splitted[[k]][which(splitted[[k]] != "")]
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+    spectrum[k,] <- splitted[[k]]
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   }
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-}
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-
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-#'
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-#'
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-#'
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-.isolate_chemical <- function(mb_record) {
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-
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-  # create empty list
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-  ch <- list()
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-
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-  # isolate chemical information
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-  ch$name <- as.list(substring(grep("CH$NAME:", mb_record, value = TRUE, fixed = TRUE), 10))
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-  ch$compound_class <- substring(grep("CH$COMPOUND_CLASS:", mb_record, value = TRUE, fixed = TRUE), 20)
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-  ch$formula <- substring(grep("CH$FORMULA:", mb_record, value = TRUE, fixed = TRUE), 13)
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-  ch$exact_mass <- as.numeric(substring(grep("CH$EXACT_MASS:", mb_record, value = TRUE, fixed = TRUE), 16))
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-  ch$smiles <- substring(grep("CH$SMILES:", mb_record, value = TRUE, fixed = TRUE), 12)
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-  ch$iupac <- substring(grep("CH$IUPAC:", mb_record, value = TRUE, fixed = TRUE), 11)
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-  ch$link_cas <- substring(grep("CH$LINK: CAS", mb_record, value = TRUE, fixed = TRUE), 14)
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-  ch$link_cayman <- substring(grep("CH$LINK: CAYMAN", mb_record, value = TRUE, fixed = TRUE), 17)
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-  ch$link_chebi <- substring(grep("CH$LINK: CHEBI", mb_record, value = TRUE, fixed = TRUE), 16)
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-  ch$link_chembl <- substring(grep("CH$LINK: CHEMBL", mb_record, value = TRUE, fixed = TRUE), 17)
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-  ch$link_chempdb <- substring(grep("CH$LINK: CHEMPDB", mb_record, value = TRUE, fixed = TRUE), 18)
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-  ch$link_chemspider <- substring(grep("CH$LINK: CHEMSPIDER", mb_record, value = TRUE, fixed = TRUE), 21)
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-  ch$link_comptox <- substring(grep("CH$LINK: COMPTOX", mb_record, value = TRUE, fixed = TRUE), 18)
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-  ch$link_hmdb <- substring(grep("CH$LINK: HMDB", mb_record, value = TRUE, fixed = TRUE), 15)
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-  ch$link_inchikey <- substring(grep("CH$LINK: INCHIKEY", mb_record, value = TRUE, fixed = TRUE), 19)
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-  ch$link_kappaview <- substring(grep("CH$LINK: KAPPAVIEW", mb_record, value = TRUE, fixed = TRUE), 20)
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-  ch$link_kegg <- substring(grep("CH$LINK: KEGG", mb_record, value = TRUE, fixed = TRUE), 15)
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-  ch$link_knapsack <- substring(grep("CH$LINK: KNAPSACK", mb_record, value = TRUE, fixed = TRUE), 19)
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-  ch$link_lipidbank <- substring(grep("CH$LINK: LIPIDBANK", mb_record, value = TRUE, fixed = TRUE), 20)
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-  ch$link_lipidmaps <- substring(grep("CH$LINK: LIPIDMAPS", mb_record, value = TRUE, fixed = TRUE), 20)
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-  ch$link_nikkaji <- substring(grep("CH$LINK: NIKKAJI", mb_record, value = TRUE, fixed = TRUE), 18)
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-  ch$link_pubchem <- substring(grep("CH$LINK: PUBCHEM", mb_record, value = TRUE, fixed = TRUE), 18)
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-  ch$link_zinc <- substring(grep("CH$LINK: ZINC", mb_record, value = TRUE, fixed = TRUE), 15)
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-
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-  # clean up data
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-  # TODO replace character(0) with NA_character
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-
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-  # return result list
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-  ch
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-}
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-
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-#'
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-#'
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-#'
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-.isolate_species <- function(mb_record) {
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-
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-  # create empty list
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-  sp <- list()
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-
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-  # species information
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-  sp$scientific_name <- substring(grep("SP$SCIENTIFIC_NAME:", mb_record, value = TRUE, fixed = TRUE), 21)
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-  sp$lineage <- substring(grep("SP$LINEAGE:", mb_record, value = TRUE, fixed = TRUE), 13)
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-  sp$link <- substring(grep("SP$LINK:", mb_record, value = TRUE, fixed = TRUE), 10)
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-  sp$sample <- substring(grep("SP$SAMPLE:", mb_record, value = TRUE, fixed = TRUE), 12)
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-  # clean up data
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-  # TODO replace character(0) with NA_character
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+  # convert to data frame and adjust data type
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+  spectrum <- as.data.frame(spectrum, stringsAsFactors = FALSE)
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+  spectrum[] <- lapply(spectrum, type.convert)
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+  colnames(spectrum) <- c("mz", "intensity", "rel.intensity")
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+
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+  # isolate spectrum metadata from record
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+  rtime <- as.numeric(substring(grep("AC$CHROMATOGRAPHY: RETENTION_TIME",
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+                                     mb,
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+                                     value = TRUE,
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+                                     fixed = TRUE),
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+                                35))
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+
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+  precursorMz <- as.numeric(substring(grep("MS$FOCUSED_ION: PRECURSOR_M/Z",
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+                                           mb,
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+                                           value = TRUE,
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+                                           fixed = TRUE),
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+                                      30))
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+
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+  precursorIntensity <- as.numeric(substring(grep("MS$FOCUSED_ION: PRECURSOR_INT",
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+                                                  mb,
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+                                                  value = TRUE,
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+                                                  fixed = TRUE),
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+                                             31))
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+
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+  title <- substring(grep("RECORD_TITLE:",
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+                          mb,
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+                          value = TRUE,
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+                          fixed = TRUE),
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+                     15)
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+
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+  # check data
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+  if(!length(precursorIntensity))
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+    precursorIntensity <- 100
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+
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+  list(rtime = rtime,
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+        scanIndex = as.integer(1),
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+        precursorMz = precursorMz,
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+        precursorIntensity = precursorIntensity,
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+        precursorCharge = as.integer(0),
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+        mz = spectrum$mz,
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+        intensity = spectrum$intensity,
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+        title = title)
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-  # return result list
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-  sp
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 }
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-#'
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-#'
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-#'
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-.isolate_analchem <- function(mb_record) {
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-
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-  # create empty list
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-  ac <- list()
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-
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-  # analytical chemistry information, MS instrument
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-  ac$instrument <- substring(grep("AC$INSTRUMENT:", mb_record, value = TRUE, fixed = TRUE), 16)
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-  ac$instrument_type <- substring(grep("AC$INSTRUMENT_TYPE:", mb_record, value = TRUE, fixed = TRUE), 21)
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-
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-  # analytical chemistry information, MS settings
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-  ac$ms_ms_type <- substring(grep("AC$MASS_SPECTROMETRY: MS_TYPE", mb_record, value = TRUE, fixed = TRUE), 31)
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-  ac$ms_cap_voltage <- substring(grep("AC$MASS_SPECTROMETRY: CAPILLARY_VOLTAGE", mb_record, value = TRUE, fixed = TRUE), 41)
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-  ac$ms_ion_mode <- substring(grep("AC$MASS_SPECTROMETRY: ION_MODE", mb_record, value = TRUE, fixed = TRUE), 32)
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-  ac$ms_col_energy <- substring(grep("AC$MASS_SPECTROMETRY: COLLISION_ENERGY", mb_record, value = TRUE, fixed = TRUE), 40)
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-  ac$ms_col_gas <- substring(grep("AC$MASS_SPECTROMETRY: COLLISION_GAS", mb_record, value = TRUE, fixed = TRUE), 37)
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-  ac$ms_desolv_gas_flow <- substring(grep("AC$MASS_SPECTROMETRY: DESOLVATION_GAS_FLOW", mb_record, value = TRUE, fixed = TRUE), 44)
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-  ac$ms_desolv_temp <- substring(grep("AC$MASS_SPECTROMETRY: DESOLVATION_TEMPERATURE", mb_record, value = TRUE, fixed = TRUE), 47)
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-  ac$ms_frag_mode <- substring(grep("AC$MASS_SPECTROMETRY: FRAGMENTATION_MODE", mb_record, value = TRUE, fixed = TRUE), 42)
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-  ac$ms_ionization <- substring(grep("AC$MASS_SPECTROMETRY: IONIZATION", mb_record, value = TRUE, fixed = TRUE), 34)
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-  ac$ms_ionization_energy <- substring(grep("AC$MASS_SPECTROMETRY: IONIZATION_ENERGY", mb_record, value = TRUE, fixed = TRUE), 41)
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-  ac$ms_laser <- substring(grep("AC$MASS_SPECTROMETRY: LASER", mb_record, value = TRUE, fixed = TRUE), 29)
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-  ac$ms_matrix <- substring(grep("AC$MASS_SPECTROMETRY: MATRIX", mb_record, value = TRUE, fixed = TRUE), 30)
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-  ac$ms_mass_accuracy <- substring(grep("AC$MASS_SPECTROMETRY: MASS_ACCURACY", mb_record, value = TRUE, fixed = TRUE), 37)
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-  ac$ms_mass_range <- substring(grep("AC$MASS_SPECTROMETRY: MASS_RANGE_MZ", mb_record, value = TRUE, fixed = TRUE), 37)
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-  ac$ms_reagent_gas <- substring(grep("AC$MASS_SPECTROMETRY: REAGENT_GAS", mb_record, value = TRUE, fixed = TRUE), 35)
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-  ac$ms_resolution <- substring(grep("AC$MASS_SPECTROMETRY: RESOLUTION", mb_record, value = TRUE, fixed = TRUE), 34)
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-  ac$ms_scan_setting <- substring(grep("AC$MASS_SPECTROMETRY: SCANNING_SETTING", mb_record, value = TRUE, fixed = TRUE), 40)
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-  ac$ms_source_temp <- substring(grep("AC$MASS_SPECTROMETRY: SOURCE_TEMPERATURE", mb_record, value = TRUE, fixed = TRUE), 42)
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-
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-  # analytical chemistry information, chromatography
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-  ac$chrom_carrier_gas <- substring(grep("AC$CHROMATOGRAPHY: CARRIER_GAS", mb_record, value = TRUE, fixed = TRUE), 32)
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-  ac$chrom_column <- substring(grep("AC$CHROMATOGRAPHY: COLUMN_NAME", mb_record, value = TRUE, fixed = TRUE), 32)
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-  ac$chrom_column_temp <- substring(grep("AC$CHROMATOGRAPHY: COLUMN_TEMPERATURE", mb_record, value = TRUE, fixed = TRUE), 39)
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-  ac$chrom_column_temp_gradient <- substring(grep("AC$CHROMATOGRAPHY: COLUMN_TEMPERATURE_GRADIENT", mb_record, value = TRUE, fixed = TRUE), 48)
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-  ac$chrom_flow_gradient <- substring(grep("AC$CHROMATOGRAPHY: FLOW_GRADIENT", mb_record, value = TRUE, fixed = TRUE), 34)
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-  ac$chrom_flow_rate <- substring(grep("AC$CHROMATOGRAPHY: FLOW_RATE", mb_record, value = TRUE, fixed = TRUE), 30)
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-  ac$chrom_inj_temp <- substring(grep("AC$CHROMATOGRAPHY: INJECTION_TEMPERATURE", mb_record, value = TRUE, fixed = TRUE), 42)
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-  ac$chrom_inj_temp_gradient <- substring(grep("AC$CHROMATOGRAPHY: INJECTION_TEMPERATURE_GRADIENT", mb_record, value = TRUE, fixed = TRUE), 51)
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-  ac$chrom_rti_kovats <- substring(grep("AC$CHROMATOGRAPHY: KOVATS_RTI", mb_record, value = TRUE, fixed = TRUE), 31)
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-  ac$chrom_rti_lee <- substring(grep("AC$CHROMATOGRAPHY: LEE_RTI", mb_record, value = TRUE, fixed = TRUE), 28)
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-  ac$chrom_rti_naps <- substring(grep("AC$CHROMATOGRAPHY: NAPS_RTI", mb_record, value = TRUE, fixed = TRUE), 29)
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-  ac$chrom_rti_uoa <- substring(grep("AC$CHROMATOGRAPHY: UOA_RTI", mb_record, value = TRUE, fixed = TRUE), 28)
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-  ac$chrom_rti_uoa_pred <- substring(grep("AC$CHROMATOGRAPHY: UOA_PREDICTED_RTI", mb_record, value = TRUE, fixed = TRUE), 38)
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-  ac$chrom_rt <- substring(grep("AC$CHROMATOGRAPHY: RETENTION_TIME", mb_record, value = TRUE, fixed = TRUE), 35)
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-  ac$chrom_rt_uoa_pred <- substring(grep("AC$CHROMATOGRAPHY: TRAMS_PREDICTED_RETENTION_TIME", mb_record, value = TRUE, fixed = TRUE), 51)
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-  ac$chrom_solvent <- as.list(substring(grep("AC$CHROMATOGRAPHY: SOLVENT", mb_record, value = TRUE, fixed = TRUE), 28))
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-  ac$chrom_transfer_temp <- substring(grep("AC$CHROMATOGRAPHY: TRANSFERLINE_TEMPERATURE", mb_record, value = TRUE, fixed = TRUE), 45)
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-
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-  # # analytical chemistry information, ion mobility
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-  # # preparation for IMS update of MassBank format
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-  # ac$ims_instrument_type <- substring(grep("AC$ION_MOBILITY: INSTRUMENT_TYPE", mb_record, value = TRUE, fixed = TRUE), 34)
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-  # ac$ims_drift_gas <- substring(grep("AC$ION_MOBILITY: DRIFT_GAS", mb_record, value = TRUE, fixed = TRUE), 28)
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-  # ac$ims_drift_time <- substring(grep("AC$ION_MOBILITY: DRIFT_TIME", mb_record, value = TRUE, fixed = TRUE), 29)
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-  # ac$ims_ccs <- substring(grep("AC$ION_MOBILITY: CCS", mb_record, value = TRUE, fixed = TRUE), 22)
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-
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-  # analytical chemistry information, general
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-  ac$general_conc <- substring(grep("AC$GENERAL: CONCENTRATION", mb_record, value = TRUE, fixed = TRUE), 27)
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-
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-  # clean up data
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-  # TODO replace character(0) with NA_character
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-
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-  # return result list
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-  ac
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-}
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-
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-#'
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-#'
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-#'
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-.isolate_massspec <- function(mb_record) {
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-
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-  # create empty list
199 
-  ms <- list()
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-
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-  # MS information, base peak
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-  ms$focus_base_peak <- substring(grep("MS$FOCUSED_ION: BASE_PEAK", mb_record, value = TRUE, fixed = TRUE), 27)
203 
-
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-  # MS information, derivative
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-  ms$focus_derivative_form <- substring(grep("MS$FOCUSED_ION: DERIVATIVE_FORM", mb_record, value = TRUE, fixed = TRUE), 33)
206 
-  ms$focus_derivative_mass <- substring(grep("MS$FOCUSED_ION: DERIVATIVE_MASS", mb_record, value = TRUE, fixed = TRUE), 33)
207 
-  ms$focus_derivative_type <- substring(grep("MS$FOCUSED_ION: DERIVATIVE_TYPE", mb_record, value = TRUE, fixed = TRUE), 33)
208 
-
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-  # MS information, precursor
210 
-  ms$focus_ion_type <- substring(grep("MS$FOCUSED_ION: ION_TYPE", mb_record, value = TRUE, fixed = TRUE), 26)
211 
-  ms$focus_precursor_int <- substring(grep("MS$FOCUSED_ION: PRECURSOR_INT", mb_record, value = TRUE, fixed = TRUE), 31)
212 
-  ms$focus_precursor_mz <- substring(grep("MS$FOCUSED_ION: PRECURSOR_MZ", mb_record, value = TRUE, fixed = TRUE), 30)
213 
-  ms$focus_precursor_type <- substring(grep("MS$FOCUSED_ION: PRECURSOR_TYPE", mb_record, value = TRUE, fixed = TRUE), 32)
214 
-
215 
-  # MS data processing
216 
-  ms$data_processing_comment <- substring(grep("MS$DATA_PROCESSING: COMMENT", mb_record, value = TRUE, fixed = TRUE), 29)
217 
-  ms$data_processing_deprofile <- substring(grep("MS$DATA_PROCESSING: DEPROFILE", mb_record, value = TRUE, fixed = TRUE), 31)
218 
-  ms$data_processing_find <- substring(grep("MS$DATA_PROCESSING: FIND_PEAK", mb_record, value = TRUE, fixed = TRUE), 31)
219 
-  ms$data_processing_reanalyze <- substring(grep("MS$DATA_PROCESSING: REANALYZE", mb_record, value = TRUE, fixed = TRUE), 31)
220 
-  ms$data_processing_recalibrate <- substring(grep("MS$DATA_PROCESSING: RECALIBRATE", mb_record, value = TRUE, fixed = TRUE), 33)
221 
-  ms$data_processing_whole <- substring(grep("MS$DATA_PROCESSING: WHOLE", mb_record, value = TRUE, fixed = TRUE), 27)
222 
-
223 
-  # clean up data
224 
-  # TODO replace character(0) with NA_character_
225 
-
226 
-  # TODO type conversion for numeric data
227 
-
228 
-  # return result list
229 
-  ms
230 
-}
231 
-
232 
-#'
233 
-#'
234 
-#'
235 
-.isolate_recordinfo <- function(mb_record) {
236 
-
237 
-  # create empty list
238 
-  recordinfo <- list()
239 
-
240 
-  # mb_record information
241 
-  recordinfo$accession <- substring(grep("ACCESSION:", mb_record, value = TRUE, fixed = TRUE), 12)
242 
-  recordinfo$deprecated <- substring(grep("DEPRECATED:", mb_record, value = TRUE, fixed = TRUE), 13)
243 
-  recordinfo$record_title <- substring(grep("RECORD_TITLE:", mb_record, value = TRUE, fixed = TRUE), 15)
244 
-  recordinfo$date <- substring(grep("DATE:", mb_record, value = TRUE, fixed = TRUE), 7)
245 
-  recordinfo$authors <- substring(grep("AUTHORS:", mb_record, value = TRUE, fixed = TRUE), 10)
246 
-  recordinfo$license <- substring(grep("LICENSE:", mb_record, value = TRUE, fixed = TRUE), 10)
247 
-  recordinfo$copyright <- substring(grep("COPYRIGHT:", mb_record, value = TRUE, fixed = TRUE), 12)
248 
-  recordinfo$publication <- substring(grep("PUBLICATION:", mb_record, value = TRUE, fixed = TRUE), 14)
249 
-  recordinfo$project <- as.list(substring(grep("PROJECT:", mb_record, value = TRUE, fixed = TRUE), 10))
250 
-
251 
-  # clean up data
252 
-  # TODO replace character(0) with NA_character_
253 
-
254 
-  # TODO type conversion for dates
255 
-
256 
-  # return result list
257 
-  recordinfo
258 
-
259 
-}
260 
-
261 
-#'
262 
-#'
263 
-#'
264 
-.isolate_peakinfo <- function(mb_record) {
265 
-
266 
-  # create empty list
267 
-  pk <- list()
268 
-
269 
-  # peak data
270 
-  pk$splash <- substring(grep("PK$SPLASH:", mb_record, value = TRUE, fixed = TRUE), 12)
271 
-  pk$num <- substring(grep("PK$NUM_PEAK:", mb_record, value = TRUE, fixed = TRUE), 14)
272 
-
273 
-  # clean up data
274 
-  # TODO replace character(0) with NA_character_
275 
-
276 
-  # TODO type conversion for numeric data
277 
-
278 
-  # return result list
279 
-  pk
280 
-
281 
-}
282 
-
283 
-#'
284 
-#'
285 
-#'
286 
-.isolate_comment <- function(mb_record) {
287 
-
288 
-  # comment section
289 
-  comment <- as.list(substring(grep("COMMENT:", mb_record, value = TRUE, fixed = TRUE), 10))
290 
-
291 
-  # return result list
292 
-  comment
293 
-
294 
-}
R/hidden_aliases.R
History View file @ 13a450d
295 115 
new file mode 100644
... ... 
@@ -0,0 +1,13 @@
1 
+#' @title Internal page for hidden aliases
2 
+#'
3 
+#' @aliases [,MsBackendDataFrame-method
4 
+#'
5 
+#' @description
6 
+#'
7 
+#' For S4 methods that require a documentation entry but only clutter the index.
8 
+#'
9 
+#' @usage NULL
10 
+#' @format NULL
11 
+#' @keywords internal
12 
+#' @docType methods
13 
+hidden_aliases <- NULL