Description Usage Arguments Details Value See Also Examples
View source: R/superPC_model_train.R
Computes feature scores for p_{path} features of a pathway via a linear model fit.
1 2 3 4 5 | superpc.train(
data,
type = c("survival", "regression", "categorical"),
s0.perc = NULL
)
|
data |
A list of test data:
|
type |
What model relates |
s0.perc |
A stabilization parameter on the interval [0,1]. This is
an internal argument to each of the called functions. The default value is
|
This function is a switch
call to
coxTrain_fun
(for type = "survival"
),
olsTrain_fun
(for type = "regression"
), or
glmTrain_fun
(for type = "categorical"
).
A list containing:
feature.scores
: The scaled p-dimensional score
vector: each value has been divided by its respective standard deviation
plus epsilon (governed by s0.perc
). NA
values returned by
the logistic model are replaced with 0.
type
: The argument for type
.
s0.perc
: The user-supplied value of s0.perc
, or the
internally-calculated default value from the chosen model.
call
: The output of match.call
for the user-
supplied function arguments.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 | # DO NOT CALL THIS FUNCTION DIRECTLY.
# Use SuperPCA_pVals() instead
## Not run:
data("colon_pathwayCollection")
data("colonSurv_df")
colon_OmicsSurv <- CreateOmics(
assayData_df = colonSurv_df[,-(2:3)],
pathwayCollection_ls = colon_pathwayCollection,
response = colonSurv_df[, 1:3],
respType = "surv"
)
asthmaGenes_char <-
getTrimPathwayCollection(colon_OmicsSurv)[["KEGG_ASTHMA"]]$IDs
data_ls <- list(
x = t(getAssay(colon_OmicsSurv))[asthmaGenes_char, ],
y = getEventTime(colon_OmicsSurv),
censoring.status = getEvent(colon_OmicsSurv),
featurenames = asthmaGenes_char
)
superpc.train(
data = data_ls,
type = "surv"
)
## End(Not run)
|
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