This function is the implementation of the two step approach for estimating surrogate
variables proposed by Leek and Storey 2007 PLoS Genetics. This function is primarily
included for backwards compatibility. Newer versions of the sva algorithm are available
svaseq, with low level functionality available
twostepsva.build(dat, mod, n.sv)
The transformed data matrix with the variables in rows and samples in columns
The model matrix being used to fit the data
The number of surogate variables to estimate
sv The estimated surrogate variables, one in each column
pprob.gam: A vector of the posterior probabilities each gene is affected by heterogeneity
pprob.b A vector of the posterior probabilities each gene is affected by mod (this is always null for the two-step approach)
n.sv The number of significant surrogate variables
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