scones.cv: Find connected explanatory SNPs.

In martini: GWAS Incorporating Networks

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")

martini documentation built on Nov. 8, 2020, 5:39 p.m.