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ggmugs: Visualization of Multiple Genome-Wide Association Study Summary Statistics

A 'grammar of graphics' approach for visualizing summary statistics from multiple Genome-wide Association Studies (GWAS). It offers geneticists, bioinformaticians, and researchers a powerful yet flexible tool for illustrating complex genetic associations using data from various GWAS datasets. The visualizations can be extensively customized, facilitating detailed comparative analysis across different genetic studies. Reference: Uffelmann, E. et al. (2021) <doi:10.1038/s43586-021-00056-9>.

Version: 0.6.0
Imports: data.table, dplyr, ggplot2, purrr, tibble, tidyr
Suggests: spelling, testthat (≥ 3.0.0)
Published: 2024-05-07
DOI: 10.32614/CRAN.package.ggmugs
Author: Wanjun Gu ORCID iD [aut, cre]
Maintainer: Wanjun Gu <wanjun.gu at ucsf.edu>
License: MIT + file LICENSE
NeedsCompilation: no
Language: en-US
Materials: README NEWS
CRAN checks: ggmugs results

Documentation:

Reference manual: ggmugs.pdf

Downloads:

Package source: ggmugs_0.6.0.tar.gz
Windows binaries: r-devel: ggmugs_0.6.0.zip, r-release: ggmugs_0.6.0.zip, r-oldrel: ggmugs_0.6.0.zip
macOS binaries: r-release (arm64): ggmugs_0.6.0.tgz, r-oldrel (arm64): ggmugs_0.6.0.tgz, r-release (x86_64): ggmugs_0.6.0.tgz, r-oldrel (x86_64): ggmugs_0.6.0.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.