Package 'MiSTr'

mist

Description

Test for association between a set of SNPS/genes and continuous outcomes by including variant characteristic information and using score statistics.

Usage

mist(
  y,
  X,
  G,
  Z,
  method = "liu",
  model = c("guess", "continuous", "binary"),
  weight.beta = NULL,
  maf = NULL
)

Arguments

y	[numeric] A numeric vector of the continuous outcome variables. Missing values are not allowed.
X	[numeric] A numeric matrix of covariates with rows for individuals and columns for covariates. If there is no covariate, it does not need to be specified
G	[numeric] A numeric genotype matrix with rows for individuals and columns for SNPs. Each SNP should be coded as 0, 1, and 2 for AA, Aa, aa, where A is a major allele and a is a minor allele. Missing genotypes are not allowed.
Z	[numeric] a numeric matrix of second level covariates for variant characteristics. Each row corresponds to a variant and each column corresponds to a variant characteristic. If there is no second level covariates, a vector of 1 should be used.
method	[character] A method to compute the p-value and the default value is "liu". Method "davies" represents an exact method that computes the p-value by inverting the characteristic function of the mixture chisq. Method "liu" represents an approximation method that matches the first 3 moments.
model	[character] A character vector specifying the model. Default is to "guess". Possible choices are "guess", "continuous" (linear regression) or "binary" (logistic regression).
weight.beta	[numeric] A numeric vector of parameters of beta function which is the weight for scorestatistics. The default value is NULL, i.e. no weight. Default weight value could be c(1, 25).
maf	[numeric] A numeric vector of MAF (minor allele frequency) for each SNP.

Value

• S.tau score Statistic for the variant heterogeneous effect.

• S.pi score Statistic for the variant mean effect.

• p.value.S.tau P-value for testing the variant heterogeneous effect.

• p.value.S.pi P-value for testing the variant mean effect.

• p.value.overall Overall p-value for testing the association between the set of SNPS/genes and outcomes. It combines p.value.S.pi and p.value.S.tau by using Fisher's procedure.

Examples

library(MiSTr)
data(mist_data)
attach(mist_data)

mist(
  y = phenotypes[, "y_taupi"],
  X = phenotypes[, paste0("x_cov", 0:2)],
  G = genotypes,
  Z = variants_info[, 1, drop = FALSE]
)

mist(
  y = phenotypes[, "y_binary"],
  X = phenotypes[, paste0("x_cov", 0:2)],
  G = genotypes,
  Z = variants_info[, 1, drop = FALSE]
)

---

mist_data

Description

mist_data

Usage

mist_data

Format

A [list] object.

Details

mist_data contains:

• phenotypes a data.frame with outcomes (continuous and binary) and covariates.

• G a numeric matrix of genotypes

• Z a numeric matrix with information on variants, i.e., group, maf and effect.

---

Print method for mist objec

Description

Print method for mist objec

Usage

## S3 method for class 'mist'
print(x, ...)

Arguments

x	[mist]
...	Other arguments (Not used).

Value

list

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