Analysis Tools

ARTP2 is an R package of biological pathway analysis or pathway meta-analysis for genome-wide association studies (GWAS). It also provides tools for gene-level test as a special case. ARTP2 is an enhanced version of two previously released packages ARTP and AdaJoint.

A panel of easy-to-interpret estimable APC functions and corresponding Wald tests in R code that can be accessed through a user-friendly web tool.

A subset-based approach improves power and interpretation for combined analysis of genetic assocation studies of heterogeneous traits.

Bayesian model for Detecting Gene Environment interaction

BSR (Bayesian Subset Regression) is an R package that implements the Bayesian subset modeling procedure for high-dimensional generalized linear models.

The Biomarker Tools set estimates risk stratification from early biomarker data and provides strategies to advance biomarkers or other risk measures identified through case-control studies to clinical or public health applications.

An R package for testing Calibration of Binary Risk Model (CBRM) using different goodness-of-fit statistics

CNVfam is a software package for jointly detecting copy number variations (CNV) in nuclear families genotyped using the Illumina platform.

CompareTests is an R package to estimate agreement and diagnostic accuracy statistics for two diagnostic tests when one is conducted on only a subsample of specimens. A standard test is observed on all specimens.

Software package designed to perform a range of association tests between sets of SNPs and a phenotype.

CGEN (Case-control.Genetics) is an R package for analyzing genetic data on case-control samples, with particular emphasis on novel methods for detecting Gene-Gene and Gene-Environment interactions.

This is a R package for rapid evaluation of extremely small p-value for resampling-based test (EXPERT).

The iCARE R Package allows researchers to quickly build models for absolute risk, and apply them to estimate an individual's risk of developing disease during a specifed time interval, based on a set of user defined input parameters.

IN.power is an R package for estimating the number of susceptibility SNPs and power of future studies.

IRRAD is an Excel spreadsheet that extends the “Axelson adjustment” for binary variables to adjust observed RRs for a confounding variable when exposure and confounder have multiple categories or to define those characteristics that a confounder must have to explain an observed association.

Background explanation of the Interactive Radioepidemiological Computer Program

Different approaches for handling varied error structures in studies of irradiated populations

LDlink is a suite of web-based applications to easily and efficiently interrogate linkage disequilibrium in population groups, with query flexibility and interactive visualization of results.

MultiAssoc is a MATLAB software package for test of association of a disease with a group of SNPs after accounting for their interaction with another group of SNPs or environmental exposures.

NestedCohort is an R software package for fitting Kaplan-Meier and Cox Models to estimate standardized survival and attributable risks for studies where covariates of interest are observed on only a sample of the cohort.

PCAmatchR is an open-source R software package that enables users to match cases and controls for more accurate GWAS analyses. It converts user-provided principal components (PC) into a Mahalanobis distance metric for selecting a set of well-matched controls for each case.

The R package and webtool fits Prevalence Incidence Mixture models to left-censored and irregularly interval-censored time to event data that is commonly found in screening cohorts assembled from electronic health records. Absolute and relative risk can be estimated for simple random sampling, and stratified sampling (the two approaches of superpopulation and a finite population are supported for target populations). Non-parametric (absolute risks only), semi-parametric, weakly-parametric (using B-splines), and some fully parametric (such as the logistic-Weibull) models are supported.

SegCNV is a software package, implemented in C++, to detect germline copy number variations in SNP array data.

Semiparametric Kernel Independence Test (SKIT) is an R package that conducts the test of independence between two vectors when there are excess zeros.