Methods


  • MetaQC: Quality control and diagnosis for microarray meta-analysis

    • A diagnosis tool for assessing quality of genomic studies for meta-analysis and determining inclusion/exclusion criteria. The "MetaQC" package is based on the following paper.

      Dongwan D. Kang, Etienne Sibille, Naftali Kaminski, and George C. Tseng*. (2011) MetaQC: Objective Quality Control and Inclusion/Exclusion Criteria for Genomic Meta-Analysis. Nucleic Acids Research. 40(2):e15.

  • MetaDE: Meta-analysis for Differential Expression Analysis

      The MetaDE package contains more than 12 popular genomic meta-analysis methods (such as Fisher, Stouffer, random effects model and fixed effects model etc.) as well as many new methods and functions developed in our lab below.

    • Adaptively weighted (AW) statistic:

      Jia Li and George C. Tseng. (2011) An adaptively weighted statistic for detecting differential gene expression when combining multiple transcriptomic studies. Annals of Applied Statistics. 5:994-1019.

    • rth ordered p-value (rOP) statistic:

      Chi Song and George C. Tseng*. (2012) Hypothesis setting and order statistic for robust genomic meta-analysis. Annals of Applied Statistics. in press.

    • Multi-class correlation (MCC) measure and ANOVA-maxP:

      Shuya Lu, Jia Li, Chi Song, Kui Shen and George C Tseng. (2010) Biomarker Detection in the Integration of Multiple Multi-class Genomic Studies. Bioinformatics. 26:333-340.

    • Meta-analysis incorporating confounding variables:

      Xingbin Wang, Yan Lin, Chi Song, Etienne Sibille* and George C Tseng*. (2012) Detecting disease-associated genes with confounding variable adjustment and the impact on genomic meta-analysis: with application to major depressive disorder. BMC Bioinformatics. 13:52.

    • Imputation for truncated p-values in genomic meta-analysis:

      Shaowu Tang and George C. Tseng*. (2013). Imputation of truncated p-values for meta-analysis methods and its genomic application. in revision.

  • MetaPath: Meta-analysis for Pathway Analysis

      The package provides gene-based and pathway-based meta-analysis for pathway analysis and also implements a new gene-based and pathway-based hybrid method described in the following paper.

    • Meta-analysis for Pathway Enrichment (MAPE):

      Kui Shen and George C. Tseng. (2010) Meta-analysis for pathway enrichment analysis when combining multiple microarray studies. Bioinformatics. 26:1316-1323.

  • MetaPCA: Meta-analysis for Dimension Reduction by PCA

      MetaPCA implements the PCA meta-analysis framework described in the following two papers.

    • MetaPCA: Meta-analysis framework for PCA:

      Sunghwan Kang, Dongwan Kang and George C. Tseng* (2013) A meta-analysis framework for principal component analysis: with applications to combining multiple transcriptomic studies. In preparation.

    • Sparse and robust MetaPCA: sparse and robust version of MetaPCA:

      Sunghwan Kang, Dongwan Kang and George C. Tseng* (2013) Sparse and robust metaPCA in genomic applications. In preparation

  • MetaClust: Meta-analysis for gene clustering (gene module identification) and sample clustering (disease subtype discovery). (under development)

    • MetaGeneClust:

      Lunching Chang and George C. Tseng (2013) Combining multiple transcriptomic studies for gene clustering. In preparation.

    • MetaSparseKmeans:

      Zhiguang Huo and George C. Tseng (2013) Meta-analysis framework of sparse K-means for disease subtype discovery when combining multiple transcriptomic studies. In preparation.

  • MetaNetwork: Meta-analysis for co-expressioin network analysis. (under development)

  • Review papers, comparative study and software papers:

    • Review paper for microarray meta-analysis
      George C. Tseng*, Debashis Ghosh and Eleanor Feingold. (2012) Comprehensive literature review and statistical considerations for microarray meta-analysis. Nucleic Acids Research 40 (9): 3785-3799.

    • Review paper for GWAS meta-analysis
      Ferdouse Begum, Debashis Ghosh, George C. Tseng*, Eleanor Feingold. (2012) Comprehensive literature review and statistical considerations for GWAS meta-analysis. Nucleic Acids Research 40 (9): 3777-3784.

    • Software paper introducing MetaQC, MetaDE and MetaPath
      Xingbin Wang, Dongwan Kang, Kui Shen, Chi Song, Shuya Lu, Lunching Chang, Serena G. Liao, Zhiguang Huo, Naftali Kaminski, Etienne Sibille, Yan Lin, Jia Li* and George C. Tseng*. (2012) A Suite of R Packages for Quality Control, Differentially Expressed Gene and Enriched Pathway Detection in Microarray Meta-analysis. Bioinformatics. 28:2534-2536.

    • Comparative study
      Lunching Chang, Huimin Lin and George C. Tseng*. (2013) Characterization and comparison of microarray meta-analysis methods. (in preparation)