Determining if and how much rare genetic variants contribute to human traits and disease is an important but complex enterprise that may be helped by a program called SimRare, developed by scientists at Baylor College of Medicine and Rice University.

"SimRare is a unified simulation platform that is a way to compare rare variant methods and design studies," said Dr. Suzanne M. Leal, professor of molecular and human genetics at Baylor and corresponding author of the report. She, along with BCM graduate students, Biao Li and Gao Wang, developed the platform to give researchers a better way to develop new methods of rare variant analysis, for estimating the statistical power of such analyses and for comparing the value of different existing methods.

General benchmark

"This enables them to use a general benchmark to compare all the methods using the same simulated dataset," said Leal, who is also on the faculty of the department of bioengineering and statistics at Rice and director of Center for Statistical Genetics at BCM.

"Developers do not have to generate their own software," she said. "They can use our software to compare the various methods."

Currently, many groups are interested in detecting associations between rare genetic variants and complex traits or diseases. New methods for detecting these associations are published monthly, and SimRare promises a way to evaluate the new methods, said Leal.

Allows comparison

"We had to do this for our own work," she said. Now she and her co-authors hope it will aid others in the field. SimRare allows comparison of the rare variant associations with generated data that uses realistic population and phenotypic models.

Funding for this work came from the National Institutes of Health.