R: ORWSS: Odds Ratio Weighted Sum Statistic

ORWSS {AssotesteR} | R Documentation

## ORWSS: Odds Ratio Weighted Sum Statistic

### Description

The ORWSS method has been proposed by Feng et al (2011) and it is based on a weighted sum statistic like the WSS method of Madsen and Browning (2009). ORWSS uses the logarithm of the odds ratio of a genetic variant as the weight for that variant, rather than the variance estimated in controls.

### Usage

      ORWSS(y, X, c.param = NULL, perm = 100)

### Arguments

`y` | numeric vector with phenotype status: 0=controls, 1=cases. No missing data allowed
`X` | numeric matrix or data frame with genotype data coded as 0, 1, 2. Missing data is allowed
`c.param` | optional value to specify the `c` parameter. See reference Feng et al, 2011
`perm` | positive integer indicating the number of permutations (100 by default)

### Details

When `c.param=NULL`, the weights of the sum statistic are simply the logarithm of the amended Odds Ratio of each variant (as in Dai et al 2012). Alternative values like `c.param=1.64` or `c.param=1.28` are suggested in Feng et al (2011).

There is no imputation for the missing data. Missing values are simply ignored in the computations.

### Value

An object of class `"assoctest"`, basically a list with the following elements:

`orwss.stat` | orwss statistic
`perm.pval` | permuted p-value
`args` | descriptive information with number of controls, cases, variants, and permutations
`name` | name of the statistic

### Author(s)

Gaston Sanchez

### References

Feng T, Elston RC, Zhu X (2011) Detecting Rare and Common Variants for Complex Traits: Sibpair and Odds Ratio Weighted Sum Statistics (SPWSS, ORWSS). Genetic Epidemiology, 35: 398-409

Dai Y, Jiang R, Dong J (2012) Weighted selective collapsing strategy for detecting rare and common variants in genetic association study. BMC Genetics, 13:7

### See Also

`WSS`

### Examples

      ## Not run:

      # number of cases
      cases = 500

      # number of controls
      controls = 500

      # total (cases + controls)
      total = cases + controls

      # phenotype vector
      phenotype = c(rep(1, cases), rep(0, controls))

      # genotype matrix with 10 variants (random data)
      set.seed(123)
      genotype = matrix(rbinom(total*10, 2, 0.05), nrow=total, ncol=10)

      # apply ORWSS with c.param=NULL and 500 permutations
      myorwss1 = ORWSS(phenotype, genotype, c.param=NULL, perm=100)
      myorwss1

      # apply ORWSS with c.param=1.64 (see Feng et al 2011)
      myorwss2 = ORWSS(phenotype, genotype, c.param=1.64, perm=100)
      myorwss2

    ## End(Not run)

[Package AssotesteR version 0.1-10 Index]