ImportLibrary {TargetSearch} | R Documentation

## Library import

### Description

These functions import a metabolite library file that will be used to processed the GC-MS data. Two file formats are supported: a tab-delimited format and the more common NIST MSP format.

### Usage

    ImportLibrary(x, type = "auto", ...)

    ImportLibrary.tab(libfile, fields = NULL, RI_dev = c(2000,1000,200),
        SelMasses = 5, TopMasses = 15, ExcludeMasses = NULL,
        libdata, file.opt=NULL)

    ImportLibrary.msp(libfile, fields = NULL, RI_dev = c(2000,1000,200),
        SelMasses = 5, TopMasses = 15, ExcludeMasses = NULL)

### Arguments

`x` | A character string or a `data.frame`. If `data.frame`, it will be passed to `ImportLibrary.tab` as parameter `libdata`. If `character`, it will be passed as `libfile` to either `ImportLibrary.tab` or `ImportLibrary.msp` according to the file type (option `type`).
`libfile` | A character string naming a library file. See details.
`type` | The library file format. Posible options are `"tab"` for a tab-delimited file, `"msp"` for NIST MSP format, or `"auto"` for autodetection. Default to `"auto"`.
`fields` | A two component list. Each component contains a regular expression used to parse and extract the fields for retention index and selection masses. Only meaningful for MSP format.
`RI_dev` | A three component vector with RI windows.
`SelMasses` | The number of selective masses that will be used.
`TopMasses` | The number of most intensive masses that will be taken from the spectrum, if no `TOP_MASS` is provided.
`ExcludeMasses` | Optional. A vector containing a list of masses that will be excluded.
`libdata` | Optional. A data frame with library data. The format is the same as the library file. It is equivalent to importing the library file first with `read.table` and calling `ImportLibrary.tab` after. This might be preferable for "fine tuning", for example, if the library file is in CSV format instead of tab-delimited.
`file.opt` | Optional. A list containing arguments to be passed to `read.table`.
`...` | Further arguments passed to `ImportLibrary.tab` or `ImportLibrary.msp`

### Details

`ImportLibrary` is a wrapper for functions `ImportLibrary.tab` and `ImportLibrary.msp` which detects automatically which function should be called.

`ImportLibrary.tab` reads a tab delimited text file by calling the function `read.table` which will be parsed and converted to a `tsLib` object. The following arguments are used by default (which are not exactly the defaults for `read.table`):

`header=TRUE, sep="\t", quote="", dec=".", fill=TRUE, comment.char="#"`

The argument `file.opt` can be used to change these options. Other alternative is to import first the file with `read.table` and friends, and call `ImportLibrary` with the resulting `data.frame`. This allows more flexibility with libraries with unusual characters, for example.

These columns are needed:

- `libID` - A unique identifier for the metabolite.

- `Name` - The metabolite name.

- `RI` - The expected RI.

- `SEL_MASS` - A list of selective masses separated with semicolon.

- `TOP_MASS` - A list of the most abundant masses to be searched, separated with semicolons.

- `Win_k` - The RI windows, k = 1,2,3. Mass search is perfomed in three steps. A RI window required for each one of them.

- `SPECTRUM` - The metabolite spectrum. m/z and intensity are separated by spaces and colons.

- `QUANT_MASS` - A list of masses that might be used for quantification. One value per metabolite and it must be one of the selective masses. (optional)

The columns `Name` and `RI` are mandatory. At least one of columns `SEL_MASS`, `TOP_MASS` and `SPECTRUM` must be given as well. By using the parameters `SelMasses` or `TopMasses` it is possible to set the selective masses or the top masses from the spectra. The parameter `ExcludeMasses` is used only when masses are obtained from the spectra. The parameter `RI_dev` can be used to set the RI windows. Note that in this case, all metabolites would have the same RI windows.

A unique identifier may be provided as well (`libID`). This could be a external database identifier. If it is not provided, a random identifier will be created of the form `GC.k`, k = 1,...,N.

The MSP format is a text file that can be imported/exported from NIST. A typical MSP file looks like this:

    Name: Pyruvic Acid
    Synon: Propanoic acid, 2-(methoxyimino)-, trimethylsilyl ester
    Synon: RI: 223090
    Synon: SEL MASS: 89|115|158|174|189
    Formula: C7H15NO3Si
    MW: 189
    Num Peaks: 41
      85    8;  86   13;  87    5;  88    4;  89  649;
      90   55;  91   28;  92    1;  98   13;  99  257;
     100  169; 101   30; 102    7; 103   13; 104    1;
     113    3; 114   35; 115  358; 116   44; 117   73;
     118   10; 119    4; 128    2; 129    1; 130   10;
     131    3; 142    1; 143   19; 144    4; 145    1;
     157    1; 158   69; 159   22; 160    4; 173    1;
     174  999; 175  115; 176   40; 177    2; 189   16;
     190    2;

    Name: another metabolite
    ...

Different entries must be separated by empty lines. In order to parse the retention time index (RI) and selective masses (SEL MASS), a two component list containing the field names of RI and SEL_MASS must be provided by using the parameter `fields`. In this example, use `field = list("RI: ", "SEL MASS: ")`. Note that `ImportLibrary` expects to find those fields next to "Synon:". Alternatively, you could provide the RI and SEL_MASS using the `tsLib` methods.

Libraries for TargetSearch and for different retention index systems, such as VAR5 or MDN35, can be downloaded from http://gmd.mpimp-golm.mpg.de/.

### Value

A `tsLib` object.

### Author(s)

Alvaro Cuadros-Inostroza, Matthew Hannah, Henning Redestig

### See Also

`ImportSamples`, `tsLib`

### Examples

    # get the reference library file
    cdfpath <- file.path(find.package("TargetSearchData"), "gc-ms-data")
    lib.file  <- file.path(cdfpath, "library.txt")

    # Import the reference library
    refLibrary <- ImportLibrary(lib.file)

    # set new names for the first 3 metabolites
    libName(refLibrary)[1:3] <- c("Metab01", "Metab02", "Metab03")

    # change the retention time deviations of Metabolite 3
    RIdev(refLibrary)[3,] <- c(3000,1500,150)

[Package TargetSearch version 1.48.0 Index]