SKATBinary_Single {SKAT} | R Documentation

## Single variant tests for binary traits with Firth and efficient resampling methods

### Description

This function computes p-values of single variant test using the firth and efficient resampling methods.

### Usage

    	SKATBinary_Single(Z, obj, method.bin="Hybrid"
    	, impute.method = "bestguess", is_check_genotype=TRUE, is_dosage = FALSE
    	, missing_cutoff=0.15, max_maf=1, estimate_MAF=1
    	, N.Resampling=2*10^6, seednum=100, epsilon=10^-6)

### Arguments

`Z` | a numeric genotype vector. Each genotype should be coded as 0, 1, 2, and 9 (or NA) for AA, Aa, aa, and missing, where A is a major allele and a is a minor allele.
`obj` | output object from SKAT_Null_Model.
`method.bin` | a type of method to compute a p-value (default="Hybrid"). See details.
`impute.method` | a method to impute missing genotypes (default= "bestguess").
`is_check_genotype` | a logical value indicating whether to check the validity of the genotype matrix Z (default= TRUE). See SKAT page for details.
`is_dosage` | a logical value indicating whether the matrix Z is a dosage matrix. If it is TRUE, SKAT will ignore “is_check_genotype”.
`missing_cutoff` | a cutoff of the missing rates of SNPs (default=0.15). Any SNPs with missing rates higher than the cutoff will be excluded from the analysis.
`max_maf` | a cutoff of the maximum minor allele frequencies (MAF) (default=1, no cutoff). Any SNPs with MAF > cutoff will be excluded from the analysis.
`estimate_MAF` | a numeric value indicating how to estimate MAFs for the weight calculation and the missing genotype imputation. See SKAT page for details
`N.Resampling` | a number of resampling to be conducted to get p-values (default=2 *10^6).
`seednum` | a seed number for random number generation (default=100). If NULL, no seed number will be assigned.
`epsilon` | a precision level (default=10^-6).

### Details

This function implements three methods (method.bin) to compute p-values: 1) Efficient resampling (ER); 2) Firth biased adjusted likelihood ratio test (Firth); and 3) Hybrid. "Hybrid" selects a method based on the total minor allele count (MAC), the number of individuals with minor alleles (m), and the degree of case-control imbalance.

Adaptive ER (ER.A) is not implemented yet.

If seednum is not NULL, set.seed(seednum) function is used to specify seeds to get the same p-values of ER based methods for different runs. Therefore, please set seednum=NULL, if you do not want to set seeds.

### Value

`p.value` | p-value. It will be the mid p-value if ER is used to compute the p-value.
`p.value.standard` | (ER only) standard p-value.
`p.value.resampling` | p-values from resampled outcome. You can obtain it when n.Resampling in SKAT_Null_Model was > 0. See the SKAT_Null_Model.
`p.value.standard.resampling` | (ER only) standard p-values from resampled outcome.
`m` | the number of individuals with minor alleles.
`MAP` | the minimum possible p-values. It is available when the method.bin="ER" and m is sufficiently small.
`MAC` | the total minor allele count (MAC).
`n.total` | (ER only) the number of resampling to be generated to get the p-value. It can be smaller than N.Resampling when the total number of configurations of case-controls among individuals with minor alleles are smaller than N.Resampling.
`is.accurate` | logical value for the accuracy of the p-value. If it is false, more resampling is needed to accurately estimate the p-value.
`method.bin` | a type of method to be used to compute the p-value.

### Author(s)

Seunggeun Lee

### References

Lee, S., Fuchsberger, C., Kim, S., Scott, L. (2015) An efficient resampling method for calibrating single and gene-based rare variant association analysis in case-control studies. Biostatistics, in press.

### Examples

    data(SKATBinary.example)
    attach(SKATBinary.example)

    obj<-SKAT_Null_Model(y ~ x1 + x2, out_type="D")
    out = SKATBinary_Single(Z[,1], obj)

    # p-value
    out$p.value

    # MAP
    out$MAP

    # method used to compute p-value (method.bin)
    out$method.bin

    #
    #	Use firth method to compute p-value
    SKATBinary_Single(Z[,1], obj, method.bin="Firth")$p.value

[Package SKAT version 1.3.2.1 Index]