View source: R/preprocessExpressionMatrix.R
preprocessExpressionMatrix | R Documentation |
This function denoises the expression matrix using the noisyR package
and then normalises it. It is recommended to use this function before using
generateShinyApp
.
preprocessExpressionMatrix( expression.matrix, denoise = TRUE, output.plot = FALSE, normalisation.method = c("quantile", "rpm", "tmm", "deseq2", "median"), n_million = 1, ... )
expression.matrix |
the expression matrix; rows correspond to genes and columns correspond to samples |
denoise |
whether to use noisyR to denoise the expression matrix; proceeding without denoising data is not recommended |
output.plot |
whether to create an expression-similarity plot for the noise analysis (printed to the console); default is FALSE |
normalisation.method |
the normalisation method to be used; default is quantile; any unrecognised input will result in no normalisation being applied, but proceeding with un-normalised data is not recommended; currently supported normalisation methods are:
|
n_million |
scaling factor for RPM normalisation; default is 1 million |
... |
optional arguments passed on to |
The denoised, normalised expression matrix; some rows (genes) may have been removed by noisyR.
expression.matrix <- as.matrix(read.csv( system.file("extdata", "expression_matrix.csv", package = "bulkAnalyseR"), row.names = 1 ))[1:10, 1:4] expression.matrix.preproc <- preprocessExpressionMatrix(expression.matrix)
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