ORWSS: ORWSS: Odds Ratio Weighted Sum Statistic

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/ORWSS.R

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

1
  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

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
  ## 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)

AssotesteR documentation built on May 2, 2019, 3:55 a.m.