search_cones: Find connected explanatory SNPs.
In hclimente/martini: GWAS Incorporating Networks

search_cones

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).

Usage

search_cones(
  gwas,
  net,
  encoding = "additive",
  sigmod = FALSE,
  covars = data.frame(),
  associationScore = c("chi2", "glm"),
  modelScore = c("stability", "bic", "aic", "aicc", "global_clustering",
    "local_clustering"),
  etas = numeric(),
  lambdas = numeric()
)

Arguments

`gwas`	A SnpMatrix object with the GWAS information.
`net`	An igraph network that connects the SNPs.
`encoding`	SNP encoding (unused argument).
`sigmod`	Boolean. If TRUE, use the Sigmod variant of SConES, meant to prioritize tightly connected clusters of 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.
`associationScore`	Association score to measure association between genotype and phenotype.
`modelScore`	String with the function to measure the quality of a split.
`etas`	Numeric vector with the etas to explore in the grid search. If ommited, it's automatically created based on the association scores.
`lambdas`	Numeric vector with the lambdas to explore in the grid search. If ommited, it's automatically created based on the association scores.

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

## Not run: gi <- get_GI_network(minigwas, snpMapping = minisnpMapping, ppi = minippi)
search_cones(minigwas, gi)
search_cones(minigwas, gi, encoding = "recessive")
search_cones(minigwas, gi, associationScore = "skat")
## End(Not run)

hclimente/martini documentation built on Feb. 26, 2024, 6:23 p.m.