Prepares a dataset for use with the
An optional character vector of length one providing some information about the expression data source.
An optional character vector of length one that lists the type of gene IDs used in the expression dataset (e.g. "Human Entrez IDs").
logical value indicating whether progress updates should be provided.
This function calculates the singular value decomposition of a gene expression
matrix and prepares the data for use with the
CMsearch function. It can
take some time for large expression matrices, and so it is recommended to save
the output for future use. Pre-processed microarray data, ready for immediate
CMsearch, can be found in the
See the CellMapper vignette for examples about how to use
associated functions to infer genes selectively expressed in specific cell
A 'CellMapperList' object ready to be provided to the
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 Biology 2016, 17(1).
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# 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 the dataset for use with CMsearch data <- CMprep(x) show(data) # Save the processed dataset for later ## Not run: save(data, file = "Preprocessed_CellMapper_Data.RData") ## End(Not run)
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