metabCombine | R Documentation |
metabCombine
wraps the five main metabCombiner
workflow steps into a single wrapper function. Parameter list arguments
organize program parameters by constituent package functions.
metabCombine(
xdata,
ydata,
binGap = 0.005,
xid = NULL,
yid = NULL,
means = list(mz = FALSE, rt = FALSE, Q = FALSE),
fitMethod = "gam",
rtOrder = TRUE,
union = FALSE,
impute = FALSE,
anchorParam = selectAnchorsParam(),
fitParam = fitgamParam(),
scoreParam = calcScoresParam(),
labelParam = labelRowsParam()
)
xdata |
metabData object. One of two datasets to be combined. |
ydata |
metabData object. One of two datasets to be combined. |
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
|
fitMethod |
RT spline-fitting method, either "gam" or "loess" |
rtOrder |
logical. If set to TRUE, retention order consistency expected
when resolving conflicting alignments for |
union |
logical. Option to include non-matched features in final
|
impute |
logical. If TRUE, imputes the mean mz/rt/Q values for missing
features in |
anchorParam |
list of parameter values for selectAnchors() function |
fitParam |
list of parameter values for fit_gam() or fit_loess() |
scoreParam |
list of parameter values for calcScores() |
labelParam |
list of parameter values for labelRows() |
The five main steps in metabCombine
are 1) m/z grouping & combined
table construction, 2) selection of ordered pair RT anchors, 3) nonlinear
spline (Basis Spline GAM or LOESS) fitting to predict RTs, 4) score
calculation and feature pair alignment ranking, 5) combined table row
annotation and reduction. metabData arguments xdata
& ydata
and m/z grouping binGap
are required for step 1.
Steps 2-5 are handled by anchors
, fit
, scores
, &
labels
, respectively, with lists containing the argument values for
each step expected for these arguments. selectAnchorsParam
,
fitgamParam
, fitloessParam
,
calcScoresParam
, & labelRowsParam
load the
default program values of selectAnchors
, fit_gam
,
fit_loess
, calcScores
& labelRows
,
respectively. These program arguments should be modified as necessary for
the datasets used for analysis.
By default, the RT fitting method (fitMethod
) is set to "gam", which
means the argument fit
is a list of parameters for fit_gam
;
if the (fitMethod
) argument is set to "loess", then the fit
argument expects a list of fit_loess
parameters.
a metabCombiner
object following complete analysis
selectAnchorsParam
, fitgamParam
,
calcScoresParam
, labelRowsParam
,
fitloessParam
data("plasma20")
data("plasma30")
p30 <- metabData(plasma30, samples = "CHEAR")
p20 <- metabData(plasma20, samples = "Red", rtmax = 17.25)
#parameter lists:
saParam <- selectAnchorsParam(tolrtq = 0.2, windy = 0.02, tolmz = 0.002)
fitParam <- fitgamParam(k = seq(12,15), iterFilter = 1, outlier = "boxplot",
family = "gaussian", prop = 0.6, coef = 1.5)
scoreParam <- calcScoresParam(A = 75, B = 15, C = 0.3)
labelParam <- labelRowsParam(maxRankX = 2, maxRankY = 2, delta = 0.1)
#metabCombine wrapper
p.combined <- metabCombine(xdata = p30, ydata = p20, binGap = 0.0075,
anchorParam = saParam, fitParam = fitParam,
scoreParam = scoreParam, labelParam = labelParam)
##to view results
p.combined.table <- combinedTable(p.combined)
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