Download Package `STARSEQ`

Package ‘STARSEQ’
February 15, 2013
Type Package
Title Secondary Trait Association analysis for Rare variants via SEQuence data
Version 1.02
Date 2012-05-15
Author Dajiang Liu
Maintainer Dajiang Liu <[email protected]>
Description STARSEQ is an R-package for detecting associations with
rare variants using selected samples in sequence-based
association studies. It corrects for the bias in the secondary
trait distribution induced by selective sampling on the primary
trait. The corrected secondary trait can be analyzed by
standard rare variant tests. In the STARSEQ package, several
popular rare variant tests were implemented, which include 1.)
combined multivariate and collapsing 2.) weighted sum
statistics, 3.) kernel based adaptive cluster, 4.) variable
threshold test 5.) sequence kernel association test.
License GPL-3
LazyLoad yes
Depends CompQuadForm,numDeriv,vcf2geno
Repository CRAN
Date/Publication 2012-08-24 19:22:18
NeedsCompilation yes
1
2
STAR-package
R topics documented:
STAR-package . . . . . . . .
cmc.uniqtl.pop . . . . . . . .
datagen.pleiomap . . . . . . .
fit.null.2nd.ex.full.pleiomap . .
kbac.uniqtl.pop.C . . . . . . .
kbac.weight . . . . . . . . . .
lse.wss.misshsq . . . . . . . .
mat2ped . . . . . . . . . . . .
meta.p . . . . . . . . . . . . .
minus.L0.2nd.ex.full.pleiomap
mySKAT . . . . . . . . . . .
recode.uniqtl . . . . . . . . .
set.compare . . . . . . . . . .
set.intersect . . . . . . . . . .
skat.uniqtl.simple.C . . . . . .
STAR.test . . . . . . . . . . .
std.score.proscore.stat.mat . .
std.score.stat.new . . . . . . .
vt.uniqtl.pop.C . . . . . . . .
wss.lin.simple.C . . . . . . . .
wss.uniqtl.pop.C . . . . . . .
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Index
STAR-package
2
3
4
4
6
6
7
8
8
9
10
10
11
11
12
12
14
14
15
16
16
18
Secondary Trait Association analysis for Rare variants via SEQuence
data
Description
STARSEQ is an R-package for detecting associations with rare variants using selected samples
in sequence-based association studies. It corrects for the bias in the secondary trait distribution
induced by selective sampling on the primary trait. The corrected secondary trait can be analyzed
by standard rare variant tests. In the STARSEQ package, several popular rare variant tests were
implemented, which include 1.) combined multivariate and collapsing 2.) weighted sum statistics,
3.) kernel based adaptive cluster, 4.) variable threshold test 5.) sequence kernel association test.
Details
Package:
Type:
Version:
Date:
License:
LazyLoad:
STAR
Package
1.0
2012-05-15
GPL-3
yes
cmc.uniqtl.pop
3
Author(s)
Dajiang Liu Maintainer: Dajiang Liu <[email protected]>
References
1. Liu, D. J. and S. M. Leal (2011). "A flexible likelihood framework for detecting associations
with secondary phenotypes in genetic studies using selected samples: application to sequence data."
Eur J Hum Genet.
2. Liu, D. J. and S. M. Leal A Unified Method for Detecting Secondary Trait Associations with
Rare Variants: Application to Sequence Data PLoS Genetics, under review
cmc.uniqtl.pop
CMC Test for Population-basd Studies of Quantitative Trait
Description
This function implements the combined multivariate and collasping method.
Usage
cmc.uniqtl.pop(dat.ped, par.dat, maf.vec, maf.cutoff, no.perm = 1000, alternative = "greater")
Arguments
dat.ped
A list of ped files.
par.dat
A list of parameters for ascertainment. The default in an empty list.
maf.vec
User specified minor allele frequency vector
maf.cutoff
Upper minor allele frequency cutoff for rare variant analysis
no.perm
The number of permutations. Set to 0 is recommended for CMC test.
alternative
Alternative hypothesis, default choice is two.sided. Other options include greater
or less.
Value
p.value
P-value as determined by the alternative hypothesis tested
statistic
Statistic value for the CMC test
Author(s)
Dajiang Liu
4
fit.null.2nd.ex.full.pleiomap
datagen.pleiomap
Simulation Function for the STARSEQ method
Description
Simulating Data for Evaluating STARSEQ package
Usage
datagen.pleiomap(pars)
Arguments
pars
A list of simulation parameters
Value
dat.ped
A list of simulated ped file
y2.vec
Simulated secondary traits
sumstat
Summary statistics calculated for simulated dataset
Author(s)
Dajiang Liu
fit.null.2nd.ex.full.pleiomap
Model Fitting Function for STARSEQ
Description
This implements the STARSEQ model for correcting the secondary trait distribution for selected
samples. This function is not intended for taking user input.
Usage
fit.null.2nd.ex.full.pleiomap(marker, rv.count.cutoff, covar.mat, y1.vec, y2.vec, yub, ylb, pct.uppe
fit.null.2nd.ex.full.pleiomap
Arguments
marker
A Matrix for marker genotypes.
rv.count.cutoff
An upper bound for collapsing variants.
covar.mat
Matrix for covariate
y1.vec
Primary trait.
y2.vec
Secondary trait.
yub
Upper trait threshold for selective sampling.
ylb
Lower trait threshold for selective sampling.
pct.upper
Upper percentage for selective sampling.
pct.lower
Lower percentage for selective sampling.
Nub
Number of samples from upper extremes.
Nlb
Number of samples from lower extremes.
Value
beta.10.est
Estimates of intercept for the primary trait
beta.11.vec.est
beta.11.vec.est is the estimates for primary trait effects
beta.20.est
beta.2y1.est
beta.20.est is the estimated intercept for secondary trait
beta.2y1.est is the estimated secondary trait effect
sigma.1.est
sigma.1.est is the estimated primary trait standard deviation
sigma.2.est
sigma.2.est is the estimated secondary trait standard deviation
beta.1z.est
beta.1z.est is the estimated covariate primary trait effect
beta.2z.est
beta.2z.est is the estimated covariate secondary trait effect
r.y1
r.y1 is the primary trait residuals
r.y2
r.y2 is the secondary trait residuals
Author(s)
Dajiang Liu
5
6
kbac.weight
KBAC Test for Population-based Studies of Quantitative Trait
kbac.uniqtl.pop.C
Description
This function implements the extended kernel-based adaptive cluster method.
Usage
kbac.uniqtl.pop.C(dat.ped, par.dat, maf.vec, maf.cutoff, no.perm = 1000, alternative = "greater")
Arguments
dat.ped
A list of ped files.
par.dat
A list of parameters for ascertainment. The default in an empty list.
maf.vec
User specified minor allele frequency vector
maf.cutoff
Upper minor allele frequency cutoff for rare variant analysis
no.perm
The number of permutations. Set to 0 is recommended for CMC test.
alternative
Alternative hypothesis, default choice is two.sided. Other options include greater
or less.
Value
p.value
P-value as determined by the alternative hypothesis tested
statistic
Statistic value for the CMC test
Author(s)
Dajiang Liu
Weighting Function for KBAC
kbac.weight
Description
Weighting function for KBAC, does not take user input
Usage
kbac.weight(dat)
Arguments
dat
Matrix format for genotype and phenotypes.
lse.wss.misshsq
7
Value
x
recoded multi-site genotypes
Author(s)
Dajiang Liu
lse.wss.misshsq
Least Square Estimates for Genetic Average Effect and Locus Heritability in the Weighted Sum Statistics
Description
Least Square Estimates for Genetic Average Effect and Locus Heritability in the Weighted Sum
Statistics
Usage
lse.wss.misshsq(marker, y, weight)
Arguments
marker
Genotype Matrix
y
Quantitative trait
weight
Weight assigned to each variant site;
Value
beta1.est
Estimates of locus genetic effects;
hsq.est
Estimates of locus genetic variance
Author(s)
Dajiang Liu
8
meta.p
Transform Mat format to PED format
mat2ped
Description
Transform Mat format data to ped format. Internal function; Not designed for user input;
Usage
mat2ped(dat.mat)
Arguments
dat.mat
Data in mat format
Value
Ped format output
Author(s)
Dajiang Liu
meta.p
P-value Based Meta-Analysis
Description
Meta-Analysis Combining P-values
Usage
meta.p(p.value.vec, N.vec, no.perm.vec, alternative = c("two.sided", "greater", "less"))
Arguments
p.value.vec
A vector of p-values from each study;
N.vec
Sample size from each study
no.perm.vec
If p-values are permutation based, the number of permutations has to be specified
alternative
Alternative hypothesis, which can be two.sided, greater or less. The default
choice is two.sided.
minus.L0.2nd.ex.full.pleiomap
9
Value
p.value
P value of meta analysis
statistic
Meta-analysis test statisitcs. The statistic is obtained by combining Z-score
statistics, which are transformed from p-values and weighted by the square root
of the sample size.
Author(s)
Dajiang Liu
minus.L0.2nd.ex.full.pleiomap
Minus Log-likelihoood Function for STAR
Description
Minus Log-likelihoood Function for STAR
Usage
minus.L0.2nd.ex.full.pleiomap(pars, marker, covar.mat, y1.vec, y2.vec, yub, ylb, pct.upper, pct.lowe
Arguments
pars
Vector of model paramters
marker
Genotype matrix
covar.mat
Matrix of covariates
y1.vec
Vector of primary traits
y2.vec
Vector of secondary traits
yub
Upper extreme primary trait cutoff for selective sampling
ylb
Lower extreme primary trait cutoff for selective sampling
pct.upper
Proportion of samples from the upper extreme
pct.lower
Proportion of samples from the lower extreme
Nub
Number of samples from the upper extreme of the primary traits
Nlb
Number of samples from lower extreme of the primary traits
Value
Returns the value for minus log likelihood, which will be used for maximum likelihood estimates.
This function is not intended to take user inputs.
Author(s)
Dajiang Liu
10
recode.uniqtl
Implementation of SKAT Test
mySKAT
Description
This implements the SKAT test according to Wu et al.
Usage
mySKAT(marker, y, W)
Arguments
marker
y
W
Marker genotypes
Vector of phenotypes
Weights calculated based the kernel used.
Value
p.value
p values from SKAT calculated based upon mixture chi-square distribution.
Author(s)
Dajiang Liu
Recode Multi-site Genotypes for KBAC Test
recode.uniqtl
Description
Record Multi-site Genotypes for KBAC Test
Usage
recode.uniqtl(dat)
Arguments
dat
Input data in matrix format;
Value
Return recoded genotypes in mat format;
Author(s)
Dajiang Liu
set.compare
set.compare
11
Comparing 2 Ordered Set of Values
Description
Compare if two ordered sets are equivalent;
Usage
set.compare(set1, set2)
Arguments
set1
set2
The first set;
The second set;
Value
1 if the two sets are equal, 0 if not;
Author(s)
Dajiang Liu
set.intersect
Calculate Intersection of Two Sets
Description
Calculate Intersection of Two Sets
Usage
set.intersect(set1, set2)
Arguments
set1
set2
A vector of set 1
A vector of set 2
Value
An intersection of Two Sets.
Author(s)
Dajiang Liu
12
STAR.test
skat.uniqtl.simple.C
SKAT Test for Population-basd Studies of Quantitative Trait
Description
This function implements the sequence kernel association test.
Usage
skat.uniqtl.simple.C(dat.ped, par.dat, maf, maf.cutoff, no.perm =
1000, alternative = "two.sided" , out.type="C")
Arguments
dat.ped
A list of ped files.
par.dat
A list of parameters for ascertainment. The default in an empty list.
maf
User specified minor allele frequency vector
maf.cutoff
Upper minor allele frequency cutoff for rare variant analysis
no.perm
The number of permutations. Set to 1000 is default for SKAT test. Adaptive
permutatoin is implemented
alternative
Alternative hypothesis, default choice is two.sided. Other options include greater
or less.
out.type
C for continuous trait
Value
p.value
P-value as determined by the alternative hypothesis tested
statistic
Statistic value for the SKAT test
Author(s)
Dajiang Liu
STAR.test
Secondary Trait Association Analysis with Rare Variants
Description
Core function for STAR
Usage
STAR.test(dat.ped, y2.vec, covar.mat, rv.count.cutoff, maf.vec, maf.cutoff, pct.upper, pct.lower, yu
STAR.test
13
Arguments
dat.ped
The list of pedigree files. Components include individual.id, family.id, genotype, phenotype, father.id, mother.id, and sex.
y2.vec
Vector of secondary trait.
covar.mat
Covariate matrix.
rv.count.cutoff
The upper bound for the very rare variants that will be collapsed in the analysis.
maf.vec
Mandatory minor allele frequencies.
maf.cutoff
The minor allele frequency threshold which is used to determine the set of variants that are analyzed.
pct.upper
Upper percentage of selection.
pct.lower
Lower percentage of selection.
yub
Upper primary trait threshold.
ylb
Lower primary trait threshold.
no.perm
Number of permutations to be performed. Default choice is 1000. Adaptive
permutation is implemented. For many tests, the asymptotic p-values can be
obtained, however, they may not be accurate.
method
Supported methods include CMC, WSS (extended by DY Lin and ZZ Tang and
by Liu and Leal), KBAC, SKAT, and VT.
alternative
Three possible alternative hypothesis two.sided, greater and less. The default
choice is two.sided. For SKAT, only two sided alternative hypothesis can be
tested
Value
p.value
P values for the specified test
statistic
Statistic values
beta.10.est
Estimates of intercept for the primary trait
beta.11.vec.est
beta.11.vec.est is the estimates for primary trait effects
beta.20.est
beta.2y1.est
beta.20.est is the estimated intercept for secondary trait
beta.2y1.est is the estimated secondary trait effect
sigma.1.est
sigma.1.est is the estimated primary trait standard deviation
sigma.2.est
sigma.2.est is the estimated secondary trait standard deviation
beta.1z.est
beta.1z.est is the estimated covariate primary trait effect
beta.2z.est
beta.2z.est is the estimated covariate secondary trait effect
r.y1
r.y1 is the primary trait residuals
r.y2
r.y2 is the secondary trait residuals
Author(s)
Dajiang J. Liu & Suzanne M. Leal
14
std.score.stat.new
std.score.proscore.stat.mat
Single Variant Score Statistics for a Genotype Matrix
Description
Single Variant Score Statistics for a Genotype Matrix
Usage
std.score.proscore.stat.mat(x.mat, y, yub, ylb, par.nuis)
Arguments
x.mat
y
yub
ylb
par.nuis
Genotype matrix
Quantitative or binary trait
Upper trait threshold
Lower trait threshold
Nuissance parameters
Value
The function returns an array of statistics
Author(s)
Dajiang Liu
std.score.stat.new
Standard Score Statistics from Prospective Likelihood
Description
Prospective Likelihood Score Statistics
Usage
std.score.stat.new(x, y, yub, ylb, par.nuis)
Arguments
x
y
yub
ylb
par.nuis
Predictor variable;
Response variable.
Upper trait threshold.
Lower trait threshold;
Other nuissance parameters;
vt.uniqtl.pop.C
15
Value
Value of statistics from the prospective likelihhod
Author(s)
Dajiang Liu
vt.uniqtl.pop.C
VT Test for Population-basd Studies of Quantitative Trait
Description
This function implements the variable threshold test
Usage
vt.uniqtl.pop.C(dat.ped, par.dat, maf.vec, maf.cutoff, no.perm = 1000, alternative = c("two.sided","
Arguments
dat.ped
A list of ped files.
par.dat
A list of parameters for ascertainment. The default in an empty list.
maf.vec
User specified minor allele frequency vector
maf.cutoff
Upper minor allele frequency cutoff for rare variant analysis
no.perm
The number of permutations. Set to 1000 is default for VT test. Adaptive permutatoin is implemented
alternative
Alternative hypothesis, default choice is two.sided. Other options include greater
or less.
Value
p.value
P-value as determined by the alternative hypothesis tested
statistic
Statistic value for the VT test
Author(s)
Dajiang Liu
16
wss.uniqtl.pop.C
wss.lin.simple.C
WSS Test for Population-basd Studies of Quantitative Trait as extended
by Lin and Tang
Description
This function implements the extended weigthed sum statisitc
Usage
wss.lin.simple.C(dat.ped, par.dat, maf.vec, maf.cutoff, no.perm = 1000, alternative = c("two.sided",
Arguments
dat.ped
A list of ped files.
par.dat
A list of parameters for ascertainment. The default in an empty list.
maf.vec
User specified minor allele frequency vector
maf.cutoff
Upper minor allele frequency cutoff for rare variant analysis
no.perm
The number of permutations. Set to 1000 is default for WSS test. Adaptive
permutatoin is implemented
alternative
Alternative hypothesis, default choice is two.sided. Other options include greater
or less.
Value
p.value
P-value as determined by the alternative hypothesis tested
statistic
Statistic value for the WSS test
Author(s)
Dajiang Liu
wss.uniqtl.pop.C
WSS Test for Population-basd Studies of Quantitative Trait
Description
This function implements the extended weigthed sum statisitc
Usage
wss.uniqtl.pop.C(dat.ped, par.dat, maf.vec, maf.cutoff, no.perm = 1000, alternative = "greater")
wss.uniqtl.pop.C
17
Arguments
dat.ped
A list of ped files.
par.dat
A list of parameters for ascertainment. The default in an empty list.
maf.vec
User specified minor allele frequency vector
maf.cutoff
Upper minor allele frequency cutoff for rare variant analysis
no.perm
The number of permutations. Set to 1000 is default for WSS test. Adaptive
permutatoin is implemented
alternative
Alternative hypothesis, default choice is two.sided. Other options include greater
or less.
Value
p.value
P-value as determined by the alternative hypothesis tested
statistic
Statistic value for the WSS test
Author(s)
Dajiang Liu
Index
cmc.uniqtl.pop, 3
datagen.pleiomap, 4
fit.null.2nd.ex.full.pleiomap, 4
kbac.uniqtl.pop.C, 6
kbac.weight, 6
lse.wss.misshsq, 7
mat2ped, 8
meta.p, 8
minus.L0.2nd.ex.full.pleiomap, 9
mySKAT, 10
recode.uniqtl, 10
set.compare, 11
set.intersect, 11
skat.uniqtl.simple.C, 12
STAR (STAR-package), 2
STAR-package, 2
STAR.test, 12
std.score.proscore.stat.mat, 14
std.score.stat.new, 14
vt.uniqtl.pop.C, 15
wss.lin.simple.C, 16
wss.uniqtl.pop.C, 16
18