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

Recent Publications

58. Kasela S,..., NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium,..., Christenson SA. Genetic and non-genetic factors affecting the expression of COVID-19-relevant genes in the large airway epithelium. Genome Med. 2021. 13(1):66.
57. Chung RH*, Chiu YF, Wang WC, Hwu CM, Hung YJ, Lee IT, Chuang LM, Quertermous T, Rotter JI, Chen YI, Chang IS, Hsiung CA. Multi-omics analysis identifies CpGs near G6PC2 mediating the effects of genetic variants on fasting glucose. Diabetologia. 2021. Apr 12.
55. Taliun D,..., NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium,...,Abecasis GR. Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program. Nature. 2021. 590(7845):290-299.
54. Nielsen JB,..., Chung RH,...,Hveem K. Loss-of-function genomic variants highlight potential therapeutic targets for cardiovascular disease. Nat Commun. 2020. 11(1):6417.
53. Reiner AP, Raffield LM, Franceschini N, Auer PL, Lange EM, Nickerson DA, Zakai NA, Correa A, Olson N; National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine Consortium; Natinal Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine Consortium. Effect of Sickle Cell Trait and APOL1 Genotype on the Association of Soluble uPAR with Kidney Function Measures in Black Americans. Clin J Am Soc Nephrol. 2021. 16(2):287-289.