Title: A Toolkit for Omics Data Visualization
Version: 1.0.5
Description: Provides a suite of tools for the comprehensive visualization of multi-omics data, including genomics, transcriptomics, and proteomics. Offers user-friendly functions to generate publication-quality plots, thereby facilitating the exploration and interpretation of complex biological datasets. Supports seamless integration with popular R visualization frameworks and is well-suited for both exploratory data analysis and the presentation of final results. Key formats and methods are presented in Huang, S., et al. (2024) "The Born in Guangzhou Cohort Study enables generational genetic discoveries" <doi:10.1038/s41586-023-06988-4>.
License: MIT + file LICENSE
URL: https://leslie-lu.github.io/
Encoding: UTF-8
Language: en-US
RoxygenNote: 7.3.2
Suggests: testthat (≥ 3.0.0), spelling
Config/testthat/edition: 3
Imports: data.table, ggbreak, ggplot2, ggrepel, ggtext, grid, magrittr, purrr, scales, showtext, sysfonts
NeedsCompilation: no
Packaged: 2025-07-15 15:35:15 UTC; luzh2
Author: Zhen Lu ORCID iD [aut, cre]
Maintainer: Zhen Lu <luzh29@mail2.sysu.edu.cn>
Repository: CRAN
Date/Publication: 2025-07-18 15:10:02 UTC

omixVizR: A Toolkit for Omics Data Visualization

Description

Provides a suite of tools for the comprehensive visualization of multi-omics data, including genomics, transcriptomics, and proteomics. Offers user-friendly functions to generate publication-quality plots, thereby facilitating the exploration and interpretation of complex biological datasets. Supports seamless integration with popular R visualization frameworks and is well-suited for both exploratory data analysis and the presentation of final results. Key formats and methods are presented in Huang, S., et al. (2024) "The Born in Guangzhou Cohort Study enables generational genetic discoveries" doi:10.1038/s41586-023-06988-4.

Author(s)

Maintainer: Zhen Lu luzh29@mail2.sysu.edu.cn (ORCID)

See Also

Useful links:

plot_qqman

Description

Create GWAS QQ & Manhattan Plots.

Usage

plot_qqman(
  plink_assoc_file,
  pheno_name,
  maf_filter = NULL,
  output_graphics = "png",
  save_plot = TRUE
)

Arguments

plink_assoc_file

Path to the PLINK association file.

pheno_name

Phenotype name.

maf_filter

Minor allele frequency filter, Default: NULL

output_graphics

Output graphics format, Default: 'png'

save_plot

Logical, whether to save plots to files. If FALSE, plots are only displayed. Default: TRUE

Details

This function reads a PLINK association file and generates Manhattan and QQ plots for the GWAS results.

Value

A list containing the ggplot objects for the Manhattan and QQ plots.

Font Information

The MetroSans font included in this package is sourced from https://fontshub.pro/font/metro-sans-download#google_vignette. It is intended for academic research and non-commercial use only. For commercial use, please contact the font copyright holder.

The font files are included in the package's inst/extdata directory and are automatically loaded for plotting.

Author(s)

Zhen Lu luzh29@mail2.sysu.edu.cn

Yanhong Liu liuyh275@mail2.sysu.edu.cn

Siyang Liu liusy99@mail.sysu.edu.cn

See Also

lulab.utils

Examples


  sample_file <- system.file("extdata", "sample_gwas.assoc.linear", package = "omixVizR")
  
  # Check if the file exists before running the example
  if (file.exists(sample_file)) {
    # Run the function with the sample data
    plots <- plot_qqman(
      plink_assoc_file = sample_file,
      pheno_name = "SamplePheno",
      save_plot = FALSE
    )
    # You can then access the plots like this:
    # print(plots$manhattan_plot)
    # print(plots$qq_plot)
  } else {
    message("Sample file not found, skipping example.")
  }