tensorflow, tibble, timeSeries, timeDate, timetk, zoo

Package: iGSEA
Type: Package
Title: Integrative Gene Set Enrichment Analysis Approaches
Version: 1.2
Date: 2017-05-07
Author: Wentao Lu, Xinlei Wang, Xiaowei Zhan
Maintainer: Wentao Lu <wlu1026@yahoo.com>
Description: To integrate multiple GSEA studies, we propose a hybrid strategy,
iGSEA-AT, for choosing random effects (RE) versus fixed effect (FE) models,
with an attempt to achieve the potential maximum statistical efficiency as
well as stability in performance in various practical situations. In addition
to iGSEA-AT, this package also provides options to perform integrative GSEA
with testing based on a FE model (iGSEA-FE) and testing based on a RE model
(iGSEA-RE). The approaches account for different set sizes when testing a
database of gene sets. The function is easy to use, and the three approaches
can be applied to both binary and continuous phenotypes.
License: GPL-2
NeedsCompilation: no
Packaged: 2017-05-12 21:50:13 UTC; zhanxw
Repository: CRAN
Date/Publication: 2017-05-12 23:12:53 UTC

Description: A collection of statistical tests for genetic association studies

Title: Genetic association tests and utilities
Description: A collection of statistical tests and utilities for

Description: A collection of statistical tests and utilities for genetic association studies

Title: Statistical Tests and Utilities for Genetic Association
Description: A collection of statistical tests for genetic association studies.

Title: Tool for sending interactive bioinformatic heatmaps with
Author: Daniel P Gaile <dpgaile@buffalo.edu>, Lori A. Shepherd
Andrew Bruno <aebruno2@ccr.buffalo.edu>, Kenneth F. Manly
Description: A tool for visualizing data

Authors@R: c(person("Daniel", "Sussman", role = c("aut", "cre"), email = "sussman@bu.edu"),
person("Zihuan", "Qiao", role = c("aut"), email = "zhqiao@bu.edu"),
person("Joshua", "Agterberg", role = "ctb"),
person("Vince", "Lyzinski", role = "ctb"))
Description: Graph matching methods and analysis. The package
works for both 'igraph' objects and matrix objects. You provide the adjacency
matrices of two graphs and some other information you might know, choose the
graph matching method, and it returns the graph matching results. 'iGraphMatch'
also provides a bunch of useful functions you might need related to graph
Suggests: dplyr (>= 0.5.0), testthat (>= 2.0.0), knitr, rmarkdown