betafam (version 1.0)

betafam: Detecting rare variants for quantitative traits uing nuclear families

Description

To detecting rare variants for quantitative traits using nuclear families, the linear combination methods are proposed using the estimated regression coefficients from the multiple regression and regularized regression as the weights.

Usage

betafam(ped,group.threshold=-1,fix.group.index=NULL, fix.weight=NULL,mute.SMM=TRUE,trait=c("binary","qtl"),LC.test=c("LC.true","LC","sig.LC","LC.mreg","LC.lasso","LC.elasticnet"),sig.LC.cutoff=0.1,true.beta=NULL,ped2multifam=FALSE,useParInRegression=FALSE,trace=FALSE)

Arguments

ped

input data, has same format with PLINK but having column names. The PED file is a white-space (space or tab) delimited file: the first six columns are mandatory: FID: Family ID; IID: Individual ID; FA: Paternal ID; MO: Maternal ID; SEX: Sex (1=male; 2=female; other=unknown); PHENO: Phenotype; Genotypes (column 7 onwards) should also be white-space delimited; they are coded as 0, 1 and 2, indicating the number of coding allele, and NA is for missing genotype.

group.threshold

optional, indicates the minor allele frequency threshold that alleles will be grouped marker in the pre-group step before the linear combination test; default is -1, which means all markers are not grouped.

fix.group.index

optional, indicates the fixed grouping index for each marker regardless of the group.threshold value. The length of this vector equals the number of markers. For example, if fix.group.index=c(1,1,2,2,2), the first two markers will be grouped and the last three will grouped together marker in the pre-group step. Default is NULL, which means no pre-group is to be done.

fix.weight

optional, indicates the fixed weight for each marker in the pre-group step. The length of this vector equals the number of markers. Default is NULL, which means the weight on each marker is automatically specified by 1/sqrt(q(1-q)), where q is the minor allele frequency.

mute.SMM

indicates whether or not the multi-marker test, same as FBAT -m test, should be calculated; default is TRUE.

trait

taking values as c("binary","qtl"),indicates the trait type, either binary ("binary") or quantitative ("qtl").

LC.test

taking values as c("LC.true","LC","sig.LC","LC.mreg","LC.lasso","LC.elasticnet"), indicates which test should be included in the linear combination methods. See details in the reference paper.

sig.LC.cutoff

indicates the pvalue threshold for grouping the markers with pvalue< sig.LC.cutoff in the sig.LC test; default is 0.

true.beta

indicates the true beta values used as the weights in the linear combination methods for simulation use only. Alternatively, this could be used as fixed weights given by the user.

ped2multifam

indicates whether or not a pedigree could be separated into multiple nuclear families. Default is FALSE.

useParInRegression

indicates whether or not parents will be used in the linear regression for estimating the weights. Default is FALSE.

trace

indicates whether or not the intermediate outcomes should be printed; default is FALSE.

Value

single.P

pvalues for the sigle marker tests.

minP

minimum pvalue for the sigle marker tests.

Z

test statistic Z=S-E(S).

Z.stat

Z statistics for each marker or group.

Zk.var

variance calculating by parental genotypes.

allele.weight

frequency-determined weights.

group.index

group index used in the pre-group step.

Ngroup

number of groups in the pre-group step.

sigma

empirical variance matrix.

inv.sigma

inverse sigma.

SMM.stat

multiple marker test statistic

SMM.pvalue

pvalue on the multiple marker test.

why.SMM.na

reason that the SMM test does not exist.

LC.beta

estimated betas in the LC test based on the single marker regression.

LC.stat

LC test statistic

LC.pvalue

pvalue on the LC test

sig.LC.beta

estimated betas in the sig.LC test.

sig.LC.stat

sig.LC test statistic

sig.LC.pvalue

pvalue on the sig.LC test

true.LC.beta

estimated betas in the true.LC test.

true.LC.stat

true.LC test statistic

true.LC.pvalue

pvalue on the true.LC test

mreg.LC.beta

estimated betas in the mreg.LC test.

mreg.LC.stat

mreg.LC test statistic

mreg.LC.pvalue

pvalue on the mreg.LC test

lasso.LC.beta

estimated betas in the lasso.LC test.

lasso.LC.stat

lasso.LC test statistic

lasso.LC.pvalue

pvalue on the lasso.LC test

elasticnet.LC.beta

estimated betas in the elasticnet.LC test.

elasticnet.LC.stat

elasticnet.LC test statistic

elasticnet.LC.pvalue

pvalue on the elasticnet.LC test

runtime

runtime of this program.

fam.info

nuclear families in the ped data.

References

Guo W , Shugart YY, Detecting Rare Variants for Quantitative Traits Using Nuclear Families (manuscript).

Examples

#example.ped<-read.table("example.ped",head=1,stringsAsFactors=F) 
#library(glmnet)
#test<-betafam(ped=example.ped,trace=TRUE)
#test$elasticnet.LC.pvalue