irwsva.build2: Adjusted irwsva.build which builds surrogate variables from...

In ttScreening: Genome-Wide DNA Methylation Sites Screening by Use of Training and Testing Samples

Description

This function is directly modified from the original irwsva.build() in the SVA package. It was noticed that under certain circumstances a subscript out of bounds error would occur while running the SVA function. Therefore, this modified code has a single line altered that conditionally uses the generic singular decomposition, svd(), instead of fast singular decomposition, fast.svd().

Usage

irwsva.build2(dat, mod, mod0 = NULL, n.sv, B = 5)

Arguments

dat	A m CpG sites by n subjects matrix of methylation data.
mod	A n by k model matrix corresponding to the primary model fit (see model.matrix)
mod0	A n by k0 model matrix corresponding to the null model to be compared to mod.
n.sv	The number of surrogate variables to construct.
B	The number of iterations of the algorithm to perform.

Details

See http://www.bioconductor.org/packages/release/bioc/manuals/sva/man/sva.pdf

Value

sv	A n by n.sv matrix where each column is a distinct surrogate variable.
pprob.gam	A vector with the posterior probability estimates that each row is affected by dependence.
pprob.b	A vector with the posterior probabiliity estimates that each row is affected by the variables in mod, but not in mod0.
n.sv	The number of suggorate variables estimated.

Note

sva Vignette http://www.biostat.jhsph.edu/~jleek/sva/

Author(s)

Original irwsva.build: Jeffrey T. Leek <[e-mail]>, John Storey [e-mail]

References

Original sva: Leek JT and Storey JD. (2008) A general framework for multiple testing dependence.Proceedings of the National Academy of Sciences, 105: 18718-18723.

Leek JT and Storey JD. (2007) Capturing heterogeneity in gene expression studies by surrogate variable analysis. PLoS Genetics, 3: e161.

ttScreening documentation built on May 2, 2019, 2:51 p.m.