| Type: | Package |
| Title: | Performs Genome-Wide Iterative Fine-Mapping for Non-Gaussian Data using GINA-X |
| Version: | 0.1.0 |
| Description: | Implements GINA-X, a genome-wide iterative fine-mapping method designed for non-Gaussian traits. It supports the identification of credible sets of genetic variants. |
| License: | GPL-3 |
| Encoding: | UTF-8 |
| LazyData: | false |
| biocViews: | Software, StatisticalMethod, VariantAnnotation |
| Imports: | GA (≥ 3.2), caret (≥ 6.0-86), memoise (≥ 1.1.0), Matrix (≥ 1.2-18), stats (≥ 4.2.2) |
| Depends: | R (≥ 4.2.0) |
| Suggests: | knitr, rmarkdown, formatR, rrBLUP, testthat (≥ 3.0.0) |
| RoxygenNote: | 7.3.2 |
| VignetteBuilder: | knitr |
| Config/testthat/edition: | 3 |
| NeedsCompilation: | no |
| Packaged: | 2025-10-08 21:08:02 UTC; xushu |
| Author: | Shuangshuang Xu 
[aut, cre],
Jacob Williams
[aut],
Allison Tegge [aut],
Marco Ferreira
[aut] |
| Maintainer: | Shuangshuang Xu <xshuangshuang@vt.edu> |
| Repository: | CRAN |
| Date/Publication: | 2025-10-14 18:20:25 UTC |
Performs GINA-X as described in the manuscript, Xu, Williams, Tegge, and Ferreira Genome-wide iterative fine-mapping for non-Gaussian data, Nature Genetics, Submitted.
Description
Performs GINA-X as described in the manuscript, Xu, Williams, Tegge, and Ferreira Genome-wide iterative fine-mapping for non-Gaussian data, Nature Genetics, Submitted.
Usage
GINAX(
Y,
Covariance,
SNPs,
family,
Z = NULL,
offset = NULL,
FDR_Nominal = 0.05,
maxiterations = 2000,
runs_til_stop = 400
)
Arguments
Y |
The observed phenotypes, count or binary. |
Covariance |
A list of covariance matrices that are the covariance matrices of the random effects. This matches the list of design matrices in Z. |
SNPs |
The SNP matrix, where each column represents a single SNP encoded as the numeric coding 0, 1, 2. This is entered as a matrix object. |
family |
Specify if the response is count ("poisson") or binary ("bernoulli"). |
Z |
A list of matrices specifying the design matrix of each random effect of interest. |
offset |
If family = "poisson", the offset of each ecotype, can be a vector or a number if the number of offset is the same for each ecotype. If family = "binomial", offset = NULL. |
FDR_Nominal |
The nominal false discovery rate for which SNPs are selected from in the screening step. |
maxiterations |
The maximum iterations the genetic algorithm in the model selection step iterates for, defaulted at 2000 |
runs_til_stop |
The number of iterations at the same best model before the genetic algorithm in the model selection step converges, defaulted at 400 |
Value
The column indices of SNPs that were in the best model identified by GINAX
Examples
data("Y_binary");data("SNPs");data("kinship")
n <- length(Y_binary)
covariance <- list()
covariance[[1]] <- kinship
## Not run:
output_binary <- GINAX(Y=Y_binary, SNPs=SNPs,
Covariance=covariance, Z=NULL, family="bernoulli",
offset=NULL, FDR_Nominal = 0.05,
maxiterations = 1000, runs_til_stop = 200)
## End(Not run)
GINAX function
Description
GINAX function
Usage
GINAX_terminal(
Y,
kinship,
Z,
SNPs,
family,
offset = NULL,
FDR.threshold,
maxiterations,
runs_til_stop
)
Value
GINAX result
PQL function
Description
PQL function
Usage
PQL(
Y,
Z,
kinship,
X = NULL,
Xc = NULL,
Xs = NULL,
indices_X = NULL,
indices_Xc = NULL,
family,
offset = NULL,
postprob = NULL
)
Value
PQL estimate
Example Dataset4: SNPs
Description
This dataset contains all SNPs.
Usage
data(SNPs)
Format
A data frame with 328 rows and 9000 variables
Source
Generated for package example
Example Dataset3: Y_binary
Description
This dataset contains response variable (binary data).
Usage
data(Y_binary)
Format
A vector for binary data
Source
Generated for package example
Example Dataset2: Y_poisson
Description
This dataset contains response variable (count data).
Usage
data(Y_poisson)
Format
A vector for poisson data
Source
Generated for package example
PQL function for binary data
Description
PQL function for binary data
Usage
binomial_PQL(Y, X_sig1 = NULL, Beta, Z, Alpha)
Value
PQL estimate for binary data
Example Dataset1: kinship
Description
This dataset contains kinship matrix.
Usage
data(kinship)
Format
A matrix for kinship
Source
Generated for package example
likelihood function
Description
likelihood function
Usage
log_marginal_likelihood(k, x.tilde_m, y.tilde, D_inv, ydinvy, dinvy, g)
Value
likelihood
likelihood function for null
Description
likelihood function for null
Usage
log_marginal_likelihood_null(y.tilde, D_inv)
Value
likelihood
PQL function for count data
Description
PQL function for count data
Usage
poisson_PQL(Y, X_sig1 = NULL, Beta, Z, Alpha, offset)
Value
PQL estimate for poisson