meta.regnorm {immunoClust} | R Documentation |
Performs a normalization via linear regression of the sample clusters in x to the clusters in y.
meta.RegNorm(y, x, method=1, alpha=0.5)
y |
immunoClust-object with the destination clusters. |
x |
immunoClust-object woth the cluster to normalize. |
method |
Alternative methods used for the normalization routine. 1 = X = a x Y 2 = X = a x Y + b |
alpha |
A value between 0 and 1 used to balance the bhattacharrya probabilities calculated with either the full covariance matrices or using only the diagonal elements of it. |
Returns the normalized cell-clusters means and co-variance matrices in a list-object with the following slots:
The number of observed parameters for the cell event clusters.
The number of cell-clustering experiments.
The N-dimensional vector with the numbers of cell event clusters in each experiment. The total number of clusters is totK = sum_{i=1}^K K_i.
The totK x P-dimensional matrix of all cluster means.
The totK x P x P-dimensional matrix of all cluster covariance matrices.
Till Sörensen till-antoni.soerensen@charite.de
data(dat.meta) data(dat.exp) dat.norm <- meta.RegNorm(dat.meta$res.clusters, dat.exp[[1]])