search_cones {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).

### 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)

[Package martini version 1.12.0 Index]