Instruction for using BARS analysis programs:

Zhang, Xiaohua, Roeder, Kathryn, Wallstrom, Garrick, Devlin, B. (2003) ,"Integration of associative statistics over genomic regions using Bayesian Adaptive Regression Splines", Human Genomics,1 : 20-29

The BARS test is built on the ideas in

DiMatteo, I. Genovese, C.R. and Kass, R.E. (2001), "Bayesian curve fitting with free-knot splines", Biometrika, 88:1055-1071

The BARS code was developed by Wallstrom and Kass

Overview:

The BARS tests is a statistical method that bridges the gap between single-locus and haplotype-based tests of association. It is based on the non-parametric regression techniques embodied by Bayesian Adaptive Regression Splines (BARS). For a set of markers falling within a common genomic region and a corresponding set of single locus association statistics, the BARS procedure integrates these results into a single test by examining the class of smooth curves consistent with the data. The non-parametric BARS procedure generally finds no signal when no liability alleles exist in the tested region (i.e., it achieves the specified size of the test) and it is sensitive enough to pick up signals when a liability allele is present. The BARS procedure provides a robust and potentially powerful alternative to classical tests of association, diminishes the multiple testing problem inherent in those tests, and can be applied to a wide range of data types, including genotype frequencies estimated from pooled samples.

This software is currently designed to perform the BARS test on data that is input as

x = Vector of locations of the genetic markers

y = Vector consisting of single locus measures of Linkage Disequilibrium between the candidate markers (in x) and the alleged liability locus. This is usually a test statistic derived from a case-control study. For example, the absolute value of the log odds ratio, divided by its standard deviation.

The main program (barsN) is implemented in the R programming language (freeware version of S-Plus) for Linux (version 1.7.0). Thus, the first step in running the program will be to download a copy of R if you do not already have it installed. To download R, go to

http://www.r-project.org/

and follow the necessary links to download R for Linux.

Once R is installed, simply type R at the command prompt to start. To quit R, type q() at the R command prompt. To cancel an R command, type control-c.

Download Executables

Download Source Code and Instructions

Instructions for Running BARS using R

Example Data sets and Results for BARS