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GPA

GPA: Genetic analysis incorporating Pleiotropy and Annotation

https://github.com/dongjunchung/gpa

Science Score: 23.0%

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    Low similarity (13.1%) to scientific vocabulary
Last synced: 11 months ago · JSON representation

Repository

GPA: Genetic analysis incorporating Pleiotropy and Annotation

Basic Info
Statistics
  • Stars: 15
  • Watchers: 3
  • Forks: 9
  • Open Issues: 1
  • Releases: 0
Created over 12 years ago · Last pushed over 6 years ago
Metadata Files
Readme

README.md

DOI

GPA

GPA (Genetic analysis incorporating Pleiotropy and Annotation) is a statistical approach to prioritizing GWAS results by integrating pleiotropy information and annotation data, proposed in Chung et al. (2014). 'GPA' package provides computationally efficient and user friendly interface to fit the GPA models and implement the hypothesis testing for the pleiotropy and the enrichment of annotation for the associated SNPs. The 'GPA' vignette provides a good start point for the step-by-step data analysis using 'GPA' package. Please check our GPA Google Group for discussions and questions regarding genetic data analysis using 'GPA' package. The following two help pages provide a good start point for the genetic analysis using the 'GPA' package, including the overview of 'GPA' package and the example command lines:

library(GPA) package?GPA class?GPA

ShinyGPA

ShinyGPA is an interactive and flexible visualization framework to investigate the pleiotropic architecture using GWAS results, proposed in Kortemeier et al. (2017). The following help page provides the overview of ShinyGPA and the example command lines:

library(GPA) ?shinyGPA

Installation

The stable versions of 'GPA' package can be obtained from the following URLs:

Package source: https://github.com/dongjunchung/GPAbinary/blob/master/GPA1.1-0.tar.gz?raw=true

Windows binary: https://github.com/dongjunchung/GPAbinary/blob/master/GPA1.1-0.zip?raw=true

Mac OS/X binary: https://github.com/dongjunchung/GPAbinary/blob/master/GPA1.1-0.tgz?raw=true

To install the developmental versions of 'GPA' package, it's easiest to use the 'devtools' package. Note that the 'GPA' package depends on the 'Rcpp' package, which also requires appropriate setting of Rtools and Xcode for Windows and Mac OS/X, respectively.

```

install.packages("devtools")

library(devtools) install_github("dongjunchung/GPA") ```

References

Chung D*, Yang C*, Li C, Gelernter J, and Zhao H (2014), "GPA: A statistical approach to prioritizing GWAS results by integrating pleiotropy information and annotation data," PLoS Genetics, 10: e1004787. (* joint first authors)

Kortemeier E, Ramos PS, Hunt KJ, Kim HJ, Hardiman G, and Chung D (2018), "ShinyGPA: An interactive and dynamic visualization toolkit for genetic studies," PLOS One, 13(1): e0190949.

Owner

  • Name: Dongjun Chung
  • Login: dongjunchung
  • Kind: user
  • Location: Columbus, OH
  • Company: The Ohio State University

GitHub Events

Total
  • Watch event: 3
  • Fork event: 1
Last Year
  • Watch event: 3
  • Fork event: 1

Committers

Last synced: over 2 years ago

All Time
  • Total Commits: 29
  • Total Committers: 2
  • Avg Commits per committer: 14.5
  • Development Distribution Score (DDS): 0.172
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Dongjun Chung d****g@g****m 24
Dongjun Chung d****g@D****l 5

Issues and Pull Requests

Last synced: 11 months ago

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  • Total issues: 0
  • Total pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Total issue authors: 0
  • Total pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
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Packages

  • Total packages: 1
  • Total downloads:
    • bioconductor 8,139 total
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 5
  • Total maintainers: 1
bioconductor.org: GPA

GPA (Genetic analysis incorporating Pleiotropy and Annotation)

  • Versions: 5
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 8,139 Total
Rankings
Dependent repos count: 0.0%
Dependent packages count: 0.0%
Average: 26.5%
Downloads: 79.4%
Maintainers (1)
dongjun.chung@gmail.com
Last synced: 11 months ago

Dependencies

DESCRIPTION cran
  • DT * depends
  • R >= 3.0.0 depends
  • Rcpp * depends
  • ggplot2 * depends
  • ggrepel * depends
  • graphics * depends
  • methods * depends
  • parallel * depends
  • plyr * depends
  • shiny * depends
  • shinyBS * depends
  • vegan * depends
  • gpaExample * suggests