王怡雯课题组

Yiwen (Eva) Wang Lab

wangyiwen@caas.cn

课题组长

王怡雯，副研究员，硕士生导师，食品科学研究中心Pre-PI。2022年获得墨尔本大学生物统计学博士学位。研究专长为针对生物学问题分析和可视化数据，同时开发针对微生物组数据分析的统计和计算方法，开发了PLSDA-batch等算法软件包。以第一作者在Briefing in Bioinformatics，Annals of the Rheumatic Diseases 等期刊发表学术论文多篇。主持中国农业科学院博士后国际交流计划引进项目、中国博士后科学基金站前特别资助、面上项目、国家自然科学基金青年科学基金项目等基金。

研究方向

针对生物学问题分析和可视化数据，同时开发针对微生物组数据分析的统计和计算方法，开发了PLSDA-batch等算法软件包。

研究内容

1）探究食品营养对肠道微生物宏基因组的影响，结合多组学整合分析，构建精准、健康的饮食结构；

2）开发提高微生物组数据分析有效性的方法，包含数据标准化、批次效应去除和表型关联的变量选择方法等。

研究进展

开发了一种基于偏最小二乘判别分析的多元非参数批次效应去除方法：PLSDA-batch。该方法能够分别估算实验和批次效应相关的潜在组分，然后去除批次效应组分；同时开发了两种扩展方法来应对不平衡的实验设计和过拟合的现象。基于此方法，研究人员可以很好地针对微生物组数据的特点来进行批次效应的去除，并得到去除后的效果评估和可视化结果。

该R包可在github上下载（https://github.com/EvaYiwenWang/PLSDAbatch）。

工作经历

2022/4 - 至今           中国农业科学院深圳农业基因组研究所    副研究员

2016/12 - 2017/7     澳大利亚昆士兰大学迪亚曼蒂纳研究所   科研助理

教育经历

2017/8 - 2022/2       墨尔本大学           生物统计学     博士

2015/3 - 2016/12     昆士兰大学           生物信息学     硕士

2008/9 - 2012/6       浙江中医药大学    生物科学        学士

PRINCIPAL INVESTIGATOR

Yiwen (Eva) Wang is an associate professor and Master's supervisor. She was awarded the degree of Ph.D in biostatistics from the University of Melbourne in 2022. Her speciality lies in solving biological problems with data analysis and visualisation, and statistical and computational methods development and implementation for microbiome studies. She has developed an R package named PLSDA-batch for batch effect correction in microbiome data analysis. As the first author, A/Prof Wang has published several peer-reviewed articles in leading journals in the bioinformatic field, including Briefing in Bioinformatics and Annals of the Rheumatic Diseases. As the chief investigator, A/Prof Wang has secured research grants from AGIS-CAAS and the National Administrative Committee of Post-Doctoral Researchers (Joint introduction program), the China Postdoctoral Science Foundation (CPSF) and the National Natural Science Foundation of China (NSFC) (Young Scientists Program).

RESEARCH INTERESTS

1) Using multi-omics integrative approaches to decipher the impact of food nutrition on gut microbial metagenome, and proposing precise and healthy dietary advice.

2) Developing novel statistical and computational methods to improve microbiome analysis, including data normalisation, batch effect management, and phenotype driving variable selection, etc.

POSITIONS AND EMPLOYMENT

2022/4 - now: Associate professor, the Food Science Center, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences

2016/12 - 2017/7: Research Assistant, University of Queensland Diamantina Institute, Woolloongabba, Australia

ACADEMIC QUALIFICATIONS

2017/8 - 2022/2: Ph.D of Biostatistics, School of Mathematics and Statistics, University of Melbourne, Australia

2015/3 - 2016/12: Master of Bioinformatics (Research Extensive), Science Faculty, University of Queensland, Australia

2008/9 - 2012/6: Bachelor of Biological Science, School of Life Science, Zhejiang Chinese Medical University, China

SELECTED PUBLICATIONS

1.Wang, Y., & Lê Cao, K. A. (2023). PLSDA-batch: a multivariate framework to correct for batch effects in microbiome data. Briefings in Bioinformatics, 24(2), bbac622.

2.Gubert, C., Choo, J. M., Love, C. J., Kodikara, S., Masson, B. A., Liew, J. J., Wang, Y., ... & Hannan, A. J. (2022). Faecal microbiota transplant ameliorates gut dysbiosis and cognitive deficits in Huntington’s disease mice. Brain communications, 4(4), fcac205.

3.Moentadj, R., Wang, Y. (co-first author), et al. (2021). Streptococcus species enriched in the oral cavity of RA patients are a source of peptidoglycan-polysaccharide polymers that can induce arthritis in mice. Annals of the Rheumatic Diseases, 80(5), 573-581.

4.Zhao, J., Han, ML., Zhu, Y., Lin, YW., Wang, Y., Lu, J., Hu, Y., Zhou, QT., Velkov, T., Li, J.(2021). Comparative metabolomics reveals key pathways associated with the synergistic activity of polymyxin B and rifampicin combination against multidrug-resistant Acinetobacter baumannii. Biochemical Pharmacology, 184, 114400.

5.Wang, Y., & Lê Cao, K. A. (2020). Managing batch effects in microbiome data. Briefings in bioinformatics, 21(6), 1954-1970.

6.Susin, A., Wang, Y., Lê Cao, K. A., & Calle, M. L. (2020). Variable selection in microbiome compositional data analysis. NAR Genomics and Bioinformatics, 2(2), lqaa029.

王怡雯课题组更新于2023年9月