Curriculum Vitae

Postdoctoral Associate
Department of Biostatistics
Yale University
300 George St. Suite 523
New Haven, CT 06520

Phone: (913) 952-8255
Google voice: (412) 450-0117


  • Ph.D. in Biostatistics, University of Pittsburgh, 2012.
    • Dissertation: Hypothesis settings and methods for gene expression meta-analysis.
    • Advisor: George C. Tseng.
  • M.S. in Biology (Bioinformatics), Tsinghua University (Beijing, China), 2007.
  • B.S. in Biology, Tsinghua University (Beijing, China), 2004.

Work Experience

  • Postdoctoral Associate, School of Public Health, Yale University, June 2012 ~ Present.
    • Advisor: Heping Zhang.
  • Graduate Student Researcher, Department of Biostatistics, University of Pittsburgh, 2008 ~ 2012.

Research Interest

Thesis Topics

  • rth Order P-value: This project investigates a robust meta-analysis hypothesis setting and develops an order statistic method.
  • Semi-parametric mixture model: This project develops a semi-parametric hierarchical Bayesian model to solve the composite null hypothesis issue in genomic meta-analysis.
  • Pan-cancer analysis: I am developing a statistical integrative framework to combine information from multiple types of genomic data (expression, genotyping, methylation, CNV, miRNA and mutation) on 15 cancer types (each containing more than 100 patients) in The Cancer Genome Atlas (TCGA) project.

Collaborative projects

  • Next-generation sequencing (NGS) project: We are studying whole-genome DNA, RNA and methylation sequencing on tumor tissues, paired blood tissues and tissues from donor to study key genetic events in tumorigenesis and disease progression. (with Dr. Jianhua Luo, Pathology, University of Pittsburgh)
  • Proteomics (MS/MS) project: We analyzed the MS/MS results of peptides with known sequences to study how the chemistry properties of the peptides affect the fragmentation process in MS/MS. (with Dr. Vicki Wysocki, Chemistry and Biochemistry, University of Arizona)
  • Prediction model for prostate cancer: We built a prediction model for prostate cancer relapse using copy number data. (with Dr. Jianhua Luo)
  • Risk score for thyroid cancer: We defined a new score to predict the aggressiveness of thyroid cancer by combining both molecular and pathological markers. (with Dr. Yuri Nikiforov, Pathology, University of Pittsburgh)


  • Student of the Year, ASA Pittsburgh Chapter, 2012.
  • Outstanding freshman scholarship II, Tsinghua University, 2000.


Peer Reviewed Journal Publications

    C. Song, X. Min, and H. Zhang. The screening and ranking algorithm for change-points detection in multiple samples. In preparation.

    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, 2014.

    C. Song and G. C. Tseng. Hypothesis setting and order statistic for robust genomic meta-analysis. The Annals of Applied Statistics, 8(2):777–800, 2014.

    Y. Xu, Y. Wu, C. Song, and H. Zhang. Simulating realistic genomic data with rare variants. Genetic epidemiology, 37(2):163–172, 2013.

    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. (* Joint first author).

    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.

    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.

    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, 2011.

    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, 2011.

    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, 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.


    C. Song and H. Zhang. Comments on “fifty years of classification and regression trees”. International Statistical Review, 2014.


    Y. Zhang, Q. Liu, Y. Guo, C. Song, J. Wang, X. Zhang, Y. Xia, Y. Cai, and X. Liu. emis: Protein modification database and flow processing system of chinese human liver proteome project. In Bioinformatics and Biomedical Engineering, 2007. ICBBE 2007. The 1st International Conference on Bioinformatics and Biomedical Engineering, pages 162–167. IEEE, 2007.


  • Prognosis prediction of prostate cancer by copy number alternation (Inventors: Jianhua Luo, Yanping Yu, Chi Song and George C. Tseng; patent pending, University Internal Reference Number 02406; patent pending)

Teaching Experience

Guest Lecturer

  • BIOST 2094: Statistical Computing in R, Spring 2011.
    • “Running R in Linux Workstation”.
  • BIOST 2078: Introductory theories and algorithms for high-throughput genomic data analysis, Fall 2011.
    • “Hidden Markov Model”.
    • “Probabilistic Graphical Models”.

Teaching Assistant

  • BIOST 2078: Introductory theories and algorithms for high-throughput genomic data analysis, Fall 2011.
    • Grading homeworks.
    • Helping preparation of course materials.

Conference Presentation

  • rth Order P-value for Microarray Meta-analysis (Contributed), JSM 2010.
  • A Tree-based Approach for Rare Variants Analysis (Invited), ICSA Joint Statistics Conference 2013.
  • Tree-based Rare Variants Analysis (Invited, presented by Dr. Heping Zhang), IMS-China 2013.
  • Tree-based Rare Variants Analysis (Contributed), JSM 2013.

Professional Experience

  • Paper reviewer for Bioinformatics, Statistics in Medicine, BMC Bioinformatics, BMC Medical Genomics, PLoS One, Statistics and Its Interface, Statistical Applications in Genetics and Molecular Biology, and Computational Statistics and Data Analysis.

Professional Society Memberships

  • American Statistical Association (ASA)
  • Eastern North American Region (ENAR) International Biometric Society
  • International Chinese Statistical Association (ICSA)

Computing Expertise

  • Statistical software: Proficient in R (package development with C/C++), Matlab.
  • Programming language: Proficient in C/C++, Java, Perl, SQL.
  • Operation system: System management of Linux, IBM AIX
  • Other: LATEX, HTML, JSP

Last updated: July 17, 2014

Chi Song,
Jul 17, 2014, 9:50 AM