CellMapperList-class: Class to contain expression data pre-processed for the...
In bradnelms/CellMapper: Predict genes expressed selectively in specific cell types

Description Details Constructor: Accessors Author(s) References See Also Examples

Container for expression data that has been pre-processed using the 'CMprep' function. A 'CellMapperList' object can be provided directly to the 'CMsearch' function to predict genes expressed selectively in specific cell types.

'CMprep' transforms an expression matrix using singular value decomposition (SVD), resulting in a matrix, 'B', with the left-singular vectors of original data matrix and a vector, 'd', with the singular values. Singular vectors that account for less variance than an individual sample in the original dataset have been trimed (Kaiser's criterion), thereby removing singular vectors that mainly account for noise. The advantage of this transformation is that it reduces dataset size, and avoids the need to perform a time-consuming SVD transformation before running 'CMsearch'.

A 'CellMapperList' object contains the transformed left singular value matrix, 'B', and singular values, 'd', as well as meta-data associated with the original expression matrix.

'CellMapperList' instances are usually created through the 'CMprep' function. See ?CMprep

To create a 'CellMapperList' object directly, the following constructor is provided:

CellMapperList(B, d, meta = list())

where B is a numeric matrix containing left-singular vectors, d is a numeric vector containing singular values, and meta is a list object containing metadata.

Same as for SimpleList objects. See ?SimpleList

The sample metadata can be extracted using metadata().

Brad Nelms

B.D. Nelms, L. Waldron, L.A. Barrera, A.W. Weflen, J.A. Goettel, G. Guo, R.K. Montgomery, M.R. Neutra, D.T. Breault, S.B. Snapper, S.H. Orkin, M.L. Bulyk, C. Huttenhower and W.I. Lencer. CellMapper: rapid and accurate inference of gene expression in difficult-to-isolate cell types. Genome Biol 2016, Accepted in Principle.

CMsearch, CMprep

# Create a mock expression dataset with random expression values
ngenes <- 1000
narrays <- 100
x <- matrix(rnorm(ngenes*narrays), ngenes, narrays)
rownames(x) <- 1:ngenes

# Prepare a CellMapperList object using the CMprep function
data <- CMprep(x, DataSource = "Mock Expression Matrix")
show(data)
metadata(data)