Chi (Chuck) Song, PhD

Chi (Chuck) Song, PhD
Assistant Professor
Phone: 614-247-8125
1841 Neil Ave.
280E Cunz Hall
Columbus, OH 43210


Dr. Song has a broad research interest in both methodological and collaborative research. He is interested in developing methods for statistical genetics and genomics, as well as methods for meta-analysis or integrative analysis of high-throughput data (e.g. ’omics data). He collaborated with physicians and biologists on various topics including cancer biology, mental health and reproductive medicine.

Research Interests:

Developing methods for statistical genetics and genomics and methods for meta-analysis or integrative analysis of high-throughput data


PhD, Biostatistics, University of Pittsburgh, 2012
MS, Biology, Tsinghua University, 2007
BS, Biology, Tsinghua University, 2004

Selected Publications:

C. Song and H. Zhang. TARV: Tree-based analysis of rare variants identifying risk modifying variants in CTNNA2 and CNTNAP2 for alcohol addiction. Genetic Epidemiology, 38(6):552–559, 2014.
Y. Xu, Y.Wu, C. Song, and H. Zhang. Simulating realistic genomic data with rare variants. Genetic Epidemiology, 37(2):163–172, 2013.
C. Song and G. C. Tseng. Hypothesis setting and order statistic for robust genomic metaanalysis. The Annals of Applied Statistics, 8(2):777–800, 2014.
X.Wang, D. Kang, K. Shen, C. Song, S. Lu, L. C. Chang, S. G. Liao, Z. Huo, S. Tang, Y. Ding, et al. An R package suite for microarray meta-analysis in quality control, differentially expressed gene analysis and pathway enrichment detection. Bioinformatics, 28(19):2534–2536, 2012.
Z. Mi, K. Shen, N. Song, C. Cheng, C. Song, N. Kaminski, and G.C. Tseng. Module-based prediction approach for robust inter-study predictions in microarray data. Bioinformatics, 26(20):2586, 2010.
S. Lu, J. Li, C. Song, K. Shen, and G.C. Tseng. Biomarker detection in the integration of multiple multi-class genomic studies. Bioinformatics, 26(3):333–340, 2010.
C. Cheng, K. Shen, C. Song, J. Luo, and G.C. Tseng. Ratio adjustment and calibration scheme for gene-wise normalization to enhance microarray inter-study prediction. Bioinformatics, 25(13):1655, 2009.
F. Tian, H. Zhang, C. Song, Y. Xia, Y.Wu, and X. Liu. miRAS: a data processing system for miRNA expression profiling study. BMC Bioinformatics, 8:285, 2007.
L.A. Qiao, J. Zhu, Q. Liu, T. Zhu, C. Song,W. Lin, G.Wei, L. Mu, J. Tao, N. Zhao, et al. BOD: a customizable bioinformatics on demand system accommodating multiple steps and parallel tasks. Nucleic Acids Research, 32(14):4175–4181, 2004.
H. Zhang, D. A. Baldwin, R. K. Bukowski, S. Parry, Y. Xu, C. Song, W. W. Andrews, G. R. Saade, M. S. Esplin, Y. Sadovsky, U. M. Reddy, J. Ilekis, M. Varner, and J. R. Biggio for the Eunice Kennedy Shriver NICHD GPN-PBR. A genomewide association study of early spontaneous preterm delivery. Genetic Epidemiology, 39(3):217-226, 2015.
Y. P. Yu*, C. Song*, G. C. Tseng, B. G. Ren, W. LaFramboise, G. Michalopoulos, J. Nelson, and J. H. Luo. Genome abnormalities precede prostate cancer and predict clinical relapse. The American Journal of Pathology, 180(6):2240–2248, 2012. (* Equal contribution).
X. Wang, Y. Lin, C. Song, E. Sibille, and G. C. Tseng. Detecting disease-associated genes with confounding variable adjustment and the impact on genomic meta-analysis: with application to major depressive disorder. BMC Bioinformatics, 13(1):1–15, 2012.
L.A. Niemeier, H. Kuffner Akatsu, C. Song, S.E. Carty, S.P. Hodak, L. Yip, R.L. Ferris, G.C. Tseng, R.R. Seethala, S.O. LeBeau, et al. A combined molecular-pathologic score improves risk stratification of thyroid papillary microcarcinoma. Cancer, 118(8):2069–2077, 2012.
W. Li, C. Song, D.J. Bailey, G.C. Tseng, J.J. Coon, and V.H.Wysocki. Statistical analysis of electron transfer dissociation pairwise fragmentation patterns. Analytical Chemistry, 83(24):9540–9545, 2011.