![]() ![]() "liu" represents an approximation method that matches the first 3 moments, "davies" represents an exact method that computes the p-value by inverting the characteristic function of the mixture chisq, See detail section.Ī method to compute the p-value (default= "davies"). Missing genotypes will be imputed by the simple Hardy-Weinberg equilibrium (HWE) based imputation.Īn output object of the SKAT_Null_Model function.Ī type of kernel (default= "linear.weighted"). ,obj.SNPWeight=NULL)Ī numeric genotype matrix with each row as a different individual and each column as a separate gene/snp.Įach 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. ![]() Is_dosage = FALSE, missing_cutoff=0.15, max_maf=1, estimate_MAF=1) thod="fixed", r.corr=0, is_check_genotype=TRUE, Method="davies", weights.beta=c(1,25), weights=NULL, Test for association between a set of SNPS/genes and continuous or dichotomous phenotypes using kernel regression framework. SNP-set (Sequence) Kernel Association Test Description SSD_FILE_OPEN: Internal variables for SSD and functions for other packages.SKAT_Null_Model_MomentAdjust: Get parameters and residuals from the NULL model for small.SKAT_Null_Model: Get parameters and residuals from the NULL model.SKAT_NULL_emmaX: Get parameters and residuals from the null model with.SKAT.haplotypes: Haplotype dataset for power calculation.SKAT_CommonRare_Robust: SNP set test (both common and rare variants) for binary.SKAT_CommonRare: SKAT for the combined effect of common and rare variants.SKAT_ChrX: SNP-set (Sequence) Kernel Association Test for X and Y.SKATBinary_Single: Single variant tests for binary traits with Firth and.SKATBinary_Robust: SNP set test for binary traits with robust region-based.SKATBinary.example: Example data for SKAT.SKATBinary: SNP set test for binary traits with asymptotic and efficient.SKAT: SNP-set (Sequence) Kernel Association Test.Resampling_FWER: Obtain significant SNP sets after controlling family wise.Read_SNP_WeightFile: Read a file with custom weights.Read_Plink_FAM: Read Plink FAM and covariates files.Power_Logistic: Power calculation, Dichotomous traits.Power_Continuous: Power calculation, continuous traits.Get_Resampling_Pvalue: Compute a resampling p-value.Get_RequiredSampleSize: Get the required sample size to achieve the given power.Get_Logistic_Weights: Get the logistic weight.Get_Genotypes_SSD: Get Genotype data from SSD file.Get_ENT: Estimate the effective number of tests for Bonferroni.Generate_SSD_SetID: Generate SNP set data file (SSD).Close_SSD: Close SNP set data file (SSD).Wu MC, Lee S, Cai T, Li Y, Boehnke M, Lin X (2011) Rare-Variant Association Testing for Sequencing Data with the Sequence Kernel Association Test. ![]() The American Journal of Human Genetics, 86: 929-942 Wu MC, Kraft P, Epstein MP, Taylor DM, Chanock SJ, Hunter DJ, Lin X (2010) Powerful SNP-Set Analysis for Case-Control Genome-wide Association Studies. For more information see reference Wu et al (2011) The second option is to specify the weights by providing a vector of weights for the variants in this case the length of the vector must equal the number of columns in X. In this case, the weights are calculated from a Beta distribution with parameters a and b. The default option ( weights=NULL) involves the calculation of the weights by taking into account the minor allele frequency of the variants. "linear" indicates the linear kernel, "wlinear" indicates a weighted linear kernel, "quadratic" indicates the quadratic polynomial kernel, "IBS" indicates Identity-By-Share, "wIBS" indicates weighted IBS, and "twowayx" indicates a two-way interaction kernel.įor the weighted kernels ( "wlinear" and "wIBS"), there are two options to get the weights. The argument kernel is used to specify the kernel function. ![]() Skat.stat skat statistic asymp.pval asymptotic p-value of the applied statistic (distributed as chi-square with df=1) perm.pval permuted p-value args descriptive information with number of controls, cases, variants, permutations, and selected kernel name name of the statistic Details Positive integer indicating the number of permutations ( NULL by default) Value "assoctest", basically a list with the following elements: ![]()
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