metabCombiner {metabCombiner} | R Documentation

## Form a metabCombiner object.

### Description

This constructs an object of type `metabCombiner` from a pair of metabolomics datasets, formatted as either `metabData` (single-dataset class) or `metabCombiner` (combined-dataset class). An initial table of possible feature pair alignments is constructed by grouping features into m/z groups controlled by the binGap argument

### Usage

    metabCombiner(
      xdata,
      ydata,
      binGap = 0.005,
      xid = NULL,
      yid = NULL,
      means = list(mz = FALSE, rt = FALSE, Q = FALSE)
    )

### Arguments

`xdata` | metabData or metabCombiner object
`ydata` | metabData or metabCombiner object
`binGap` | numeric parameter used for grouping features by m/z. See ?mzGroup for more details.
`xid` | character identifier of xdata. If xdata is a metabData, assigns a new ID for this dataset; if xdata is a metabCombiner, must be assigned to one of the existing dataset IDs. See details for more information.
`yid` | character identifier of ydata. If ydata is a metabData, assigns a new ID for this dataset; if ydata is a metabCombiner, must be assigned to one of the existing dataset IDs. See details for more information.
`means` | logical. Option to take average m/z, rt, and/or Q from `metabComber`. May be a vector (length = 3), a single value (TRUE/FALSE), or a list with names "mz", "rt", "Q" as names.

### Details

This function serves as a constructor of the `metabCombiner` combined dataset class and the entry point in the main workflow for pairwise dataset alignment. Two arguments must be specified, `xdata` and `ydata`, which must be both `metabData` objects, both `metabCombiner` objects, or one `metabData` and one `metabCombiner`. Each scenario is listed here:

1) If xdata & ydata are `metabData` objects, a new `metabCombiner` object is constructed with an alignment of this pair. New character identifiers are assigned to each dataset (xid & yid, respectively); if these are unassigned, then "1" and "2" will be their respective ids. xdata & ydata will be the active "dataset x" and "dataset y" used for the paired alignment.

2) If xdata is a `metabCombiner` and ydata is a `metabData`, then the result is the existing `metabCombiner` xdata augmented by an additional dataset, ydata. One set of meta-data (id, m/z, rt, Q, adduct labels) from xdata is used for alignment with the respective information from ydata, which is controlled by the `xid` argument; see the `datasets` method for extracting existing dataset ids. A new identifier yid is assigned to ydata, which must be distinct from the current dataset identifier.

3) If xdata is a `metabData` and ydata is a `metabCombiner`, then a similar process to #2 occurs, with xdata augmented to the existing ydata object and one of the constitutent dataset's meta-data is accessed, as controlled by the yid argument. One major difference is that rts of ydata serve as the "reference" or dependent variable in the spline-fitting step.

4) If xdata and ydata are both `metabCombiner` objects, the resulting `metabCombiner` object aligns information from both combined datasets. As before, one set of values contained in xdata (specified by xid argument) is used to align to the values from ydata (controlled by yid argument). The samples and extra columns are concatenated from all datasets.

For `metabCombiner` object inputs, the mean of the numeric fields (m/z, rt, Q) from all constituent datasets can be used in alignment in place of values from a single dataset. These are controlled by the means argument. By default this is a list value with "mz", "rt" and "Q" as names, but may also accept a sinle logical or a length-3 logical vector. If set to a single logical, then all three fields are averaged (TRUE) or not averaged (FALSE). If a three-length argument is supplied (e.g. c(TRUE, FALSE, FALSE)), then the values correspond to m/z, rt, and Q respectively.

### Value

a `metabCombiner` object constructed from xdata and ydata, with features grouped by m/z according to the binGap argument.

### Note

If using a `metabCombiner` object as input, only one row is allowed per feature corresponding to its first appearance. It is strongly recommended to reduce the table to 1-1 paired matches prior to aligning it with a new dataset.

### Examples

    data(plasma30)
    data(plasma20)

    p30 <- metabData(plasma30, samples = "CHEAR")
    p20 <- metabData(plasma20, samples = "Red", rtmax = 17.25)

    p.comb = metabCombiner(xdata = p30, ydata = p20, binGap = 0.0075,
                           xid = "p30", yid = "p20")

[Package metabCombiner version 1.2.2 Index]