Description Usage Arguments Value Examples
Normalize a training dataset so that each array shares a same median and store the median from the training dataset as the reference to frozen median normalize a test dataset. Also two other options are available: to only normalize a training dataset but not frozen normalize a test dataset, or vise versa.
1 |
train |
the training dataset to be median normalized.
The dataset must have rows as probes and columns as samples.
This can be left unspecified if |
test |
the test dataset to be frozen median normalized.
The dataset must have rows as probes and columns as samples.
The number of rows must equal to the number of rows in the training set.
By default, the test set is not specified ( |
ref.dis |
the reference distribution for frozen median normalize test set
against previously normalized training set.
This is required when |
a list of two datasets and one reference distribution:
train.mn |
the normalized training set, if training set is specified |
test.fmn |
the frozen normalized test set, if test set is specified |
ref.dis |
the reference distribution |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | set.seed(101)
group.id <- substr(colnames(nuhdata.pl), 7, 7)
train.ind <- colnames(nuhdata.pl)[c(sample(which(group.id == "E"), size = 64),
sample(which(group.id == "V"), size = 64))]
train.dat <- nuhdata.pl[, train.ind]
test.dat <- nuhdata.pl[, !colnames(nuhdata.pl) %in% train.ind]
# normalize only training set
data.mn <- med.norm(train = train.dat)
str(data.mn)
# normalize training set and frozen normalize test set
data.mn <- med.norm(train = train.dat, test = test.dat)
str(data.mn)
# frozen normalize test set with reference distribution
ref <- med.norm(train = train.dat)$ref.dis
data.mn <- med.norm(test = test.dat, ref.dis = ref)
str(data.mn)
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