Selected methodology publications by Statistical Facility staff
- Scoring of ChIP-seq experiments by modeling large-scale correlated tests
Pingzhao Hu, Zhi Wei, Zhouzhi Wang, Andrew D Paterson, Joseph Beyene, Steve W Scherer Proceedings of Critical Assessment of Massive Data Analysis (CAMDA), October, 2009,
Chicago, USA. - Using the ratio of means as the effect size measure in combining results of microarray experiments
Pingzhao Hu, Celia MT Greenwood and Joseph Beyene
BMC Systems Biology 2009, 3:106 - A flexible approximate likelihood ratio test for detecting differential expression in microarray data
Ahmed Hossain, Joseph Beyene, Andrew R. Willana, and Pingzhao Hu
Computational Statistics & Data Analysis 2009, 53:3685-3695. - Identifying cis- and trans-acting single-nucleotide polymorphisms controlling lymphocyte gene expression in humans.
Pingzhao Hu, Hui Lan, Wei Xu, Joseph Beyene, Celia MT Greenwood
BMC Proc. 2007; 1 Suppl 1:S7.
Top 10 most viewed articles of all time - Integrative analysis of gene expression data including an assessment of pathway enrichment for predicting prostate cancer.
Pingzhao Hu, Celia MT Greenwood and Joseph Beyene
Cancer Informatics. 2007; 2:289-300. - Optimal selection of markers for validation or replication from genome-wide association studies.
Greenwood CM, Rangrej J, Sun L.
Genet Epidemiol. 2007;31:396-407. - A hierarchical clustering method for estimating copy number variation.
Xing B, Greenwood CM, Bull SB.
Biostatistics. 2007;8:632-53. - Tests for differential gene expression using weights in oligonucleotide microarray experiments.
Pingzhao Hu, Joseph Beyene and Celia MT Greenwood
BMC Genomics. 2006; 7:33. - Statistical methods for meta-analysis of microarray data: a comparative study
Pingzhao Hu, Celia MT Greenwood and Joseph Beyene
Information Systems Frontiers 2006; 8:9-20. - Integrative analysis of multiple gene expression profiles with quality-adjusted effect size models.
Pingzhao Hu, Celia MT Greenwood and Joseph Beyene
BMC Bioinformatics. 2005; 6:128.