limma_screen: Screening procedure based on LIMMA
In methyvim: Targeted, Robust, and Model-free Differential Methylation Analysis

Reduces the methytmle object by way of a limma model with empirical Bayes shrinkage to include only the CpG sites below the preset p-value cutoff. INTERNAL USE ONLY.

1	limma_screen(methytmle, var_int, type, cutoff = 0.05)

`methytmle`	An object of class `methytmle`.
`var_int`	A `numeric` vector containing subject-level measurements of the variable of interest. The length of this vector must match the number of subjects exactly. If argument `vim` is set to "ate" or "rr", then the variable of interest is treated as an exposure, and the variable must be binary in such cases. If setting `vim` to target parameters assessing continuous treatment effects, then the variable need not be binary of course.
`type`	Character indicating the particular measure of DNA methylation to be used as the observed data in the estimation procedure, either Beta values or M-values. The data are accessed via `minfi::getBeta` or `minfi::getM`.
`cutoff`	Numeric indicating the p-value cutoff that defines which sites pass through the `filter`.

An object of class methytmle, that is a subset of the original methytmle input object which has been reduced include only the relevant CpG sites. This subset is then used to estimate VIMs.

methyvim documentation built on Nov. 8, 2020, 11:11 p.m.