Bridge: a GUI Software for Genetic Risk Prediction
Bridge is built for both designing and analyzing a risk prediction model. In the design stage, it provides an estimated classification accuracy of the model and determines the sample size required to verify this accuracy. In the analysis stage, it adopts a robust and powerful algorithm for forming the risk prediction model.
Download
| File name | Download | Description |
|---|---|---|
| Bridge | Bridge_1.0.zip | R GUI software for genetic risk prediction (version 1.0) |
| Installing script | install.R | A R script to install Bridge software. In order to appropriate install Bridge, we suggest users to first install a recent R version (>= 3.0.0.) |
| Bridge vignette | Bridge.pdf | User manual (version 1.0) |
GWGGI: Genome-Wide Gene-Gene Interaction Analysis
GWGGI is C++ software for genome-wide gene-gene interaction analyses . GWGGI utilizes tree-based algorithms to search a large number of genetic markers for disease-associated joint association with the consideration of high-order interactions, and then uses non-parametric statistics to test the joint association.
Download
| Platform | File | Version |
|---|---|---|
| Unix | gwggi.unix.zip | v1.0 |
| Windows | gwggi.win.zip | v1.0 |
| C++ source | gwggi.code.zip | v1.0 |
MLR: R code for genetic risk prediction allowing for phenotypic heterogeneity
MLR iteratively determines homogenous sub-phenotype groups, and builds a parsimonious risk prediction model for each sub-phenotype group.
Download
| File name | Download | Description |
|---|---|---|
| MLR | Code.zip | R code |
| Example | Example.R | a simple example of running the programs |
| Readme | Readme.txt | Readme file |
FB_GGRF: R code for genetic association analysis of family-based sequencing Data
FB_GGRF utilizes a generalized genetic random field method for the statistical analysis of family-based sequencing data.
Download
| File name | Download | Description |
|---|---|---|
| FB_GGRF | Code.zip | R code |
| Example | Example.R | a simple example of running the programs |
FU: R code for functional data analysis of sequencing Data
FU first constructs smooth functions from individuals’ sequencing data, and then tests the association of these functions with multiple phenotypes by using a U-statistic.
Download
| File name | Download | Description |
|---|---|---|
| FU | FU | R code |
| Example | Example | a simple example of running the programs |
GGRF: R code for genetic association analysis of sequencing Data by using a generalized genetic random field method
GGRF utilizes a generalized genetic random field method for the statistical analysis of sequencing data. It accommodates a variety of disease phenotypes (e.g., quantitative and binary phenotypes), and can be applied to small-scale sequencing data without need for small-sample adjustment.
Download
| File name | Download | Description |
|---|---|---|
| GGRF | function.r | R code |
| Example | Example.zip | a simple example of running the program |
| Readme | Readme.txt | Readme file |