View source: R/metabCombiner.R
This constructs an object of type
metabCombiner from a pair of
metabolomics datasets, formatted as either
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
metabCombiner( xdata, ydata, binGap = 0.005, xid = NULL, yid = NULL, means = list(mz = FALSE, rt = FALSE, Q = FALSE), rtOrder = TRUE, impute = FALSE )
metabData or metabCombiner object
metabData or metabCombiner object
numeric parameter used for grouping features by m/z. See ?mzGroup for more details.
character. If xdata is a
character. If ydata is a
logical. Option to take average m/z, rt, and/or Q from
logical. If set to TRUE, retention order consistency expected
when resolving conflicting alignments for
logical. If TRUE, imputes the mean mz/rt/Q values for missing
This function serves as a constructor of the
dataset class and the entry point to the main workflow for pairwise dataset
alignment. Two arguments must be specified,
which must be either
There are four scenarios listed here:
1) If xdata & ydata are
metabData objects, a new
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
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
3) If xdata is a
metabData and ydata is a
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.
metabCombiner object inputs, the full workflow
labelRows) must be performed before
further alignment. If not completed already, features are pared down to
1-1 alignments via the resolveConflicts approach (see: help(resolveRows)).
Features may not be used more than twice and will be removed if they are
detected as duplicates.
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 single logical or a length-3 logical vector. If set to a single logical value, 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. RT averaging is generally not recommended for disparate data alignment.
If missing features have been incorporated into the
they an be imputed using the average m/z, rt, and Q values for that feature
in datasets in which it is present by setting
impute to TRUE.
Likewise, this option is not recommended for disparate data alignment.
metabCombiner object constructed from xdata and ydata, with
features grouped by m/z according to the binGap argument.
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.
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")
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.