# NOT RUN {
# Data with features in columns
data(rosenwald)
group <- rosenwald.cli$group
expr <- t(rosenwald.expr)
# All features, all samples
k <- LPS.coeff(data=expr, response=group)
k <- LPS.coeff(formula=group~1, data=as.data.frame(expr))
### LPS.coeff(formula=group~., data=as.data.frame(expr), na.action=na.pass)
### The last is correct but (really) slow on large datasets
# Feature subset, all samples
k <- LPS.coeff(data=expr[, c("27481","17013") ], response=group)
k <- LPS.coeff(formula=group~`27481`+`17013`, data=as.data.frame(expr))
### Notice backticks in formula for syntactically invalid names
# All features, sample subset
training <- rosenwald.cli$set == "Training"
### training <- sample.int(nrow(expr), 10)
### training <- which(rosenwald.cli$set == "Training")
### training <- rownames(subset(rosenwald.cli, set == "Training"))
k <- LPS.coeff(data=expr, response=group, subset=training)
k <- LPS.coeff(formula=group~1, data=as.data.frame(expr), subset=training)
# NA handling by model.frame()
k <- LPS.coeff(formula=group~1, data=as.data.frame(expr), na.action=na.omit)
# }
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