学术讲座预告

时  间：5月5日(周五)下午3:00-4:00

地  点：育才校区数学楼3楼会议室

主讲人：复旦大学生物统计研究中心  张洪博士

主  题：Adjusting for Non-Confounding Risk Factors in Genetic Association Studies Using Case-Control Data

摘  要：In  literature,  there  is  debate  on  whether  non-confounding  covariates  should  be  adjusted  in  genetic  association  studies  using  case-control data. Some argue that adjusting for non-confounding covariates can lose  power  when  the  disease  prevalence  is  small  while  some  argue  that doing  so  can  improve  power  when  the  disease  prevalence  is  large.  To effectively  exploit  non-confounding  covariates,  we  develop  a  modified profile  likelihood  method  that  is  computationally  stable  compared  with competing  methods  for  detecting  disease  associated  genetic  variants. Theoretical  attempts  shows  that  the  proposed  method  is  asymptotically  more powerful than the standard logistic regression method with or without adjusting  for  non-confounding  covariates,  no  matter  what  the  disease prevalence is. The desired properties are demonstrated through extensive simulation studies and a real data example. We extend the proposed method to analyze case-control mother-offspring data, which achieves even larger power gain against the existing methods.

主讲人简介：

    个人主页: http://homepage.fudan.edu.cn/zhangh/ 
    张洪，男，1975年出生。1993年9月-1997年7月，中国科学技术大学数学系本科生，获理学学士；1997年9月-2000年7月，中国科学技术大学数学系研究生，获理学硕士学位；2001年2月-2003年12月，中国科学技术大学统计与金融系博士研究生，获理学博士学位。2000年7月-2003年12月，中国科学技术大学统计与金融系助教；2004年1月-2008年12月，中国科学技术大学统计与金融系讲师；2004年3月-2005年4月，美国乔治华盛顿大学统计系，博士后研究；2006年8月-2007年11月，美国耶鲁大学医学院，博士后研究；2009年1月-2010年12月，美国国立卫生研究院，博士后研究；2010年12月被聘为复旦大学生命科学学院正高级青年PI、研究员。主要研究方向 (Research Interests) 为高通量基因数据的统计方法学研究；生存分析；医学统计。

代表性成果：

1.Wang C, Shen Q, Du L, Xu J, Zhang H# (2016). armDNA: A functional beta model for detecting age-related genomewide DNA methylation marks. Statistical Methods in Medical Research (Accepted). (Wang C is my Ph.D. student)

 Du Li, Wang Yulong, Zhang Hang, Zhang Hong, Gao Ying (2016). Folate in take and risk of endometrial cancer: A meta-analysis. Oncotarget (Accepted). (Du Li is my graduate student.)

2.Kang G, Du L, Zhang H# (2016). multiDE: A dimension reduced model based statistical method for differential expression analysis using RNA-sequencing data from multiple conditions. BMC Bioinformatics 17: 248. (Kang G was my graduate student)

3.Shen Q, Hu J, Jiang N, Hu X, Luo Z, Zhang H#(2016). contamDE: Differential expression analysis of RNA-seq data for contaminated tumor samples. Bioinformatics 32(5): 705-712. (Shen Q was my Ph. D. student)

4.Hu J, Li T, Xiu Z, Zhang H (2015). MAFsnp: A Multi-sample Accurate and Flexible SNP Caller Using Next-generation Sequencing Data. PLoS ONE 10(8): e0135332. doi:10.1371/journal.pone.0135332. (Hu J was my Ph. D. student)

5.Zhang H, Xu J, Jiang N, Hu X, Luo Z (2015). PLNseq: a multivariate Poisson lognormal distribution for high-throughput matched RNA-sequencing read count data. Statistics in Medicine 34: 1577-1589.

6.Zhang H, Qin J, Landi M, Caporaso N, Yu K (2013). A copula-model based semiparametric interaction test under the case-control design. Statistica Sinica. 23: 1505-1521

7.Zhang H, Zeng D, Olschwangd S, Yu K (2013). Semiparametric inference on the penetrances of rare genetic mutations based on a case-family design. Journal of Statistical Planning and Inference. 143: 368-377.

8.Zhang H, Wacholder S, Qin J, Hildesheim A, Yu K (2011). Improved genetic association tests for an ordinal outcome representing the disease progression process. Genetic Epidemiology. 35: 499-505.

9.Li T, Li Z, Ying Z, Zhang H#. (2010). Influence of population stratification on population based marker-disease association analysis. Annals of Human Genetics. 74:351-360.

10.Zhang H, Olschwang S, Yu K. (2010). Statistical inference on the penetrances of rare genetic mutations based on a case-family design. Biostatistics. 11:519-532.

Z11.hang H, Chen H, Li Z. (2009). Large sample interval mapping method for genetic trait loci in finite regression mixture models. Journal of Statistical Planning and Inference. 139:764-779.

12.Yan T, Yang Y, Cheng X, DeAngelis MM, Hoh J, Zhang H# (2009). Genotypic association analysis using discordant-relative-pairs. Annals of Human Genetics. 73:84-94.

13.Chen K*, Ying Z*, Zhang H*, Zhao L* (2008). Analysis of least absolute deviation. Biometrika. 95:107-122.

14.Zhang Han, Zhang Hong#, Li Zhaohai, Zheng Gang (2007). Statistical methods for haplotype-based matched case-control association studies. Genetic Epidemiology. 31: 316-326.

15.Zhang H, Zheng G, Li Z (2006). Statistical analysis for haplotype-based matched casecontrol studies. Biometrics, 62:1124-1131.