Title: MetaDE: Microarray meta-analysis for differentially expressed
Author: Xingbin Wang, Jia Li and George C Tseng
Description: MetaDE package implements 12 major meta-analysis methods

Title: Meta analysis of multiple microarray data
Maintainer: Jia Li<jiajiaysc@gmail.com> and Xingbin
Description: A collection of functions for conducting genomic

Description: An ensemble meta-prediction framework to integrate multiple regression
models into a current study. Gu, T., Taylor, J.M.G. and Mukherjee, B. (2020)
A meta-analysis framework along with two weighted estimators as the ensemble
of empirical Bayes estimators, which combines the estimates from the different
external models. The proposed framework is flexible and robust in the ways
that (i) it is capable of incorporating external models that use a slightly
different set of covariates; (ii) it is able to identify the most relevant
external information and diminish the influence of information that is less
compatible with the internal data; and (iii) it nicely balances the bias-variance
trade-off while preserving the most efficiency gain. The proposed estimators
are more efficient than the naive analysis of the internal data and other
naive combinations of external estimators.
person(given = "Tian", family = "Gu", role = c("aut"), email = "gutian@umich.edu"),
person(given = "Bhramar", family = "Mukherjee", role = c("aut"), email = "bhramar@umich.edu"),
person(given = "Michael", family = "Kleinsasser", role = c("cre"), email = "mkleinsa@umich.edu")

Title: MetaIntegrator- Meta-Analysis of Gene Expression Data
Author: Winston A. Haynes, Francesco Vallania, Aurelie Tomczak, Timothy Sweeney,
Maintainer: Winston A. Haynes <hayneswa@stanford.edu>
Description: A pipeline for the meta-analysis  of gene expression data. We have
assembled several analysis and plot functions to
perform integrated multi-cohort analysis of gene expression data (meta-
Imports: rmeta, multtest, ggplot2, parallel, Rmisc, reshape, gplots,
Biobase, RMySQL, DBI, stringr, preprocessCore, GEOquery,
Suggests: BiocStyle, knitr, rmarkdown, RUnit, BiocGenerics