A novel estimator of between-study variance in random-effects models
作者: Nan WangJun ZhangLi XuJing QiBeibei LiuYiyang TangYinan JiangLiang ChengQinghua JiangXunbo YinShuilin Jin
作者单位: 1School of Mathematics, Harbin Institute of Technology, Harbin, Heilongjiang, China
2Rehabilitation department, Heilongjiang Province Land Reclamation Headquarters General Hospital, Harbin, Heilongjiang, China
3College of Computer Science and Technology, Harbin Engineering University, Harbin, Heilongjiang, China
4School of Mathematics, Heilongjiang University, Harbin, Heilongjiang, China
5Heilongjiang Province Hospital of Chinese Medicine, Harbin, Heilongjiang, China
6College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China
7School of Life Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang, China
刊名: BMC Genomics, 2020, Vol.21 (1), pp.287-308
来源数据库: Springer Nature Journal
DOI: 10.1186/s12864-020-6500-9
关键词: Differentially expressed genesBetween-study varianceRandom-effects modelMeta-analysis
英文摘要: Abstract(#br)Background(#br)With the rapid development of high-throughput sequencing technologies, many datasets on the same biological subject are generated. A meta-analysis is an approach that combines results from different studies on the same topic. The random-effects model in a meta-analysis enables the modeling of differences between studies by incorporating the between-study variance. Results(#br)This paper proposes a moments estimator of the between-study variance that represents the across-study variation. A new random-effects method (DSLD2), which involves two-step estimation starting with the DSL estimate and the D g 2...
全文获取路径: Springer Nature  (合作)
影响因子:4.397 (2012)