Software

We have developed a variety of software that have been used for genetic, genomic and more generally, biomedical research. We have programs that are broadly distributed, have broad academic, research and commercial uses and perform reliably and precisely according to the computing demands of end-users. Additionally, we have programs that need more work and testing and others that are fully developed. Below are the programs th at we have developed with a brief description of each:

AAOT — Association Analysis of an Ordinal Trait

This is an SAS program that converts an ordinal trait to a quantitative trait, and prepares a data set that can be fed into FBAT for association analysis.

CTMBR — Classfication Trees for Multiple Binary Responses

This is a program to construct classification trees for multiple binary responses. In Biomedical Research, many diagnoses are based on multiple items such as depression and anxiety. This program makes it possible to conduct analysis at the item level.

eLASSO — Robust Variable Selection Using Exponential Squared Loss

A number of Matlab codes are provided for the implementation of eLASSO.

HapForest — Forest for Detecting Haplotypes and Interactions among Them in Association with a Disease

This program implements a forest-based approach to accommodate the haplotype uncertainties and variable importance to sort out significant haplotypes and their interactions in genomewide case-control association studies.

LOT - Linkage Analysis of Ordinal Traits

This program performs linkage analysis of ordinal traits for pedigree data. It implements a latent-variable proportional-odds logistic model that relates inheritance patterns to the distribution of the ordinal trait.

MASAL — Multivariate Adaptive Splines for Analysis of Longitudinal Data

The standalone program takes a data structure similar to that of "CTMBR", except that there is a time variable "t". We also have an R package.

modSaRa — Modified Screening and Ranking Algorithm to Detect Chromosome Copy Number Variations

This is a program using modified screening and ranking algorithm to detect chromosome copy number variations. It is an optimal and accurate approach solving practical issues regarding CNV detection.

multiSaRa — A Screening and Ranking Algorithm to Detect Chromosome Copy Number Variations in Multiple Sequences

This is a program that enhances the screening and ranking algorithm to detect chromosome copy number variations in multiple sequences.

pLASSO — prior LASSO

We provide two R functions to run pLASSO.

RTREE — Classification Trees for Risk Profile and Diagnosis

Program that analyzes relative risk and conducts sib pair linkage analysis using tree-based methods. This program can be executed to automatically generate a tree structure or allow the user to construct a tree of his or her choice.

SaRa — Screening and Ranking Algorithm to Detect Chromosome Copy Number Variations

This is a program to detect chromosome copy number variations. It is fast and possesses optimal theoretical properties.

simuRare — Simulating Realistic Genomic Data with Rare Variants

simuRare a regression-based algorithm that imputes rare variants in currently available SNP array data, and performs a resampling approachto simulate samples that contain both common and rare SNPs.

STREE — Survival Analysis Trees

Represents one of the most popular uses of tree-based methods. This program identifies prognostic factors that are predictive of survival outcome and time to an event of interest. It partitions a study sample into strata to reveal distinct patt erns of survival among subgroups.

TARV — Tree-based Analysis of Rare Variants

TARV is a tree-based method to explore the association between rare variants and complex diseases, and find potential genetic and environmental factors and their interactions.

Twin Analysis — Twin Analysis Using SAS

This program uses SAS PROC NLMIXED and PROC MIXED to conduct twin analysis to estimate heritability of binary and quantitative traits.

Willows

This is a software package that includes three classifiers: classification tree, random forest, and deterministic forest. This package is built on RTREE mainly to implement the most efficient memory use for SNP