scones.cv {martini} | R Documentation

## Find connected explanatory SNPs.

### Description

Finds the SNPs maximally associated with a phenotype while being connected in an underlying network (Azencott et al., 2013). Select the hyperparameters by cross-validation.

### Usage

    scones.cv(gwas, net, covars = data.frame(), ...)

### Arguments

`gwas` | A SnpMatrix object with the GWAS information.
`net` | An igraph network that connects the SNPs.
`covars` | A data frame with the covariates. It must contain a column 'sample' containing the sample IDs, and an additional columns for each covariate.
`...` | Extra arguments for `parse_scones_settings`.

### Value

A copy of the `SnpMatrix$map` `data.frame`, with the following additions:

- c: contains the univariate association score for every single SNP.

- selected: logical vector indicating if the SNP was selected by SConES or not.

- module: integer with the number of the module the SNP belongs to.

### References

Azencott, C. A., Grimm, D., Sugiyama, M., Kawahara, Y., & Borgwardt, K. M. (2013). Efficient network-guided multi-locus association mapping with graph cuts. Bioinformatics, 29(13), 171-179. https://doi.org/10.1093/bioinformatics/btt238

### Examples

    gi <- get_GI_network(minigwas, snpMapping = minisnpMapping, ppi = minippi)
    scones.cv(minigwas, gi)
    scones.cv(minigwas, gi, score = "glm")

[Package martini version 1.6.0 Index]