apply.LTR: Apply a fitted LTR model to a new dataset
In LTR: Perform LTR analysis on microarray data

Description Usage Arguments Details Value Author(s) References Examples

Map a gene-expression matrix into the space encoded by a linear-tranformation of replicates (LTR) fit object.

1	apply.LTR(x, model.fit);

`x`	A matrix with samples as columns and genes as rows; must have the same number of rows as the model in model.fit
`model.fit`	A list with components rownames, intercepts, slopes, r.squared, and residuals. Exactly such a list is generated by fit.LTR

x must have the same number of rows (and in the same order) as the components of model.fit – no validation of this is performed.

A gene-expression matrix of dim(x) in the space of model.fit

Paul C. Boutros

The LTR paper, once published

x <- matrix(nrow = 100, ncol = 10, data = rnorm(1000));
y <- matrix(nrow = 100, ncol = 10, data = rnorm(1000));
model.fit <- fit.LTR(x, y);

z <- apply.LTR(
	x = y + matrix(nrow = 100, ncol = 10, data = rnorm(1000) / 10),
	model.fit = model.fit
	);