tempo.runInstance: Build models for all pathways using the control data and test...
In tempoR: Characterizing Temporal Dysregulation

Description Usage Arguments Value Examples

Build models for all pathways using the control data and test on the test population.

1 2	tempo.runInstance(X, Y, genesets, ctrl, test, train = NULL, comps = 10, validation = "CV")

`X`	a matrix with sample ids as row names and gene ids as column names.
`Y`	a list indexed by sample ids, containing numerical values.
`genesets`	a list of lists. Outer list is indexed by gene set name, inner list contains all gene ids in a given gene set
`ctrl`	a list of sample ids. The list of control samples to use in scoring.
`test`	a list of sample ids. The list of test samples to use in scoring.
`train`	a list of sample ids. The list of control samples to train models on. If null, train on ctrl.
`comps`	maximum number of components to use in the plsr model
`validation`	"CV" for 10-fold cross-validation, "LOO" for leave-one-out cross-validation. "CV" is nondeterministic and should not be used where exactly reproducible results are important

a list with the following entries

ctrl a list of the sample names used from the control set used for scoring
test a list of the sample names used from the test set used for scoring
train a list of the sample names used from the control set to train models
scores a data frame with gene set ids as row names and a "ctrlMSE" and "score" entry for each gene set with the MSE of control age predictions in cross-validation and the calulated score, respectively
pred a matrix with gene set labels, where the age prediction for sample j from the models for gene set i are at i,j
Y the continuous variable of interest that models are built with respect to, e.g. age
genesets the gene sets used in the analysis

data("dflatExample")
data("gse32472Example")

# It is possible to run just the model-building and scoring functions and skip
# cross-validation.  This is not recommended for general use, but may be useful
# in some cases
results = tempo.runInstance(ctrl=gse32472Example$ctrl,
    test=gse32472Example$test,
    genesets=dflatExample,
    X=gse32472Example$data,
    Y=gse32472Example$age)