About Lab Research

Dr. Ren-Hua Chung’s Lab focus on three research areas: statistical method development for genetic data, software development for genetic data analysis, and complex disease association analysis. We are developing novel statistical association tests, which aim to identify candidate genes associated with complex diseases based on human genetics data. We are particularly interested in developing family-based association tests. These tests include single-variant tests, gene-based tests, pathway analysis methods, and gene-gene interaction methods. With the high-throughput technique to generate genetic data, it has become important to develop efficient software to analyze the big data. We are developing efficient software packages that integrate difference resources such as public databases, bioinformatics tools, and statistical methods for genetic data analysis. Moreover, we are involved in several complex disease studies, such as metabolic syndrome, hypertension, and schizophrenia research.

Recent Software Release

FamPipe
FamPipe is an automatic analysis pipeline for analyzing sequencing data in families for disease studies. Access the pipeline at http://fampipe.sourceforge.net
GESDB
GESDB is a platform for sharing simulation data and discussion of simulation techniques for human genetic studies. Access the database at http://gesdb.nhri.org.tw
SeqSIMLA2_exact
SeqSIMLA2 -exact efficiently simulates genotypes conditional on disease status. Download the software from http://seqsimla.sourceforge.net
GCORE
GCORE is an efficient family-based gene-gene interaction test for trios. Download the software from http://gscore.sourceforge.net
OPTPDT
OPTPDT is a family-based multi-SNP association test using an optimal p-value threshold algorithm for GWAS. Download the software from http://optpdt.sourceforge.net