| Type: | Package |
| Title: | Visualization of Multiple Genome-Wide Association Study Summary Statistics |
| Version: | 0.6.0 |
| Description: | 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>. |
| License: | MIT + file LICENSE |
| Encoding: | UTF-8 |
| Suggests: | spelling, testthat (≥ 3.0.0) |
| Config/testthat/edition: | 3 |
| Imports: | data.table, dplyr, ggplot2, purrr, tibble, tidyr |
| Language: | en-US |
| RoxygenNote: | 7.3.1 |
| NeedsCompilation: | no |
| Packaged: | 2024-05-06 19:14:04 UTC; wanjun |
| Author: | Wanjun Gu  [aut,
cre] |
| Maintainer: | Wanjun Gu <wanjun.gu@ucsf.edu> |
| Repository: | CRAN |
| Date/Publication: | 2024-05-07 08:00:07 UTC |
Visualizing Multiple Genetic Studies
Description
This function processes and combines summary statistics from multiple genetic studies and creates a visualization for all studies. The genetic loci are colored based on three significance thresholds to facilitate the visualization of highly significant genomic regions.
Usage
ggmugs(
study_name = c("sumstat1", "sumstat2", "sumstat3", "sumstat4", "sumstat5"),
summary_stat = c("data/sumstat1.txt", "data/sumstat2.txt", "data/sumstat3.txt",
"data/sumstat4.txt", "data/sumstat5.txt"),
p1 = 0.001,
p2 = 5e-05,
p3 = 1e-08,
color1 = "#FFFFE0",
color2 = "#FFC300",
color3 = "#FF5733"
)
Arguments
study_name |
A character vector of names for the studies. |
summary_stat |
A character vector of file paths where each path points to the summary statistics data file for the corresponding study. Files should be in a tabular format readable by 'fread' from the 'data.table' package. The files should contain 3 fields: 'chr' (Chromosome), 'pos' (chromosome position), and 'p' (association p-value). The positions of multiple GWAS summary statistics should have consistent genome builds. |
p1 |
The first significance level threshold for p-values (default is 1e-3). |
p2 |
The second, more stringent significance level threshold for p-values (default is 5e-5). |
p3 |
The most stringent significance level threshold for p-values (default is 1e-8). |
color1 |
The color for points below the first significance level (default is "#FFFFE0"). |
color2 |
The color for points between the first and second significance levels (default is "#FFC300"). |
color3 |
The color for points above the second significance level (default is "#FF5733"). |
Value
A 'ggplot' object representing the visualization with the specified data.
Examples
### NOT RUN
# ggmugs(
# study_name = c("study1", "study2", "study3", "study4", "study5"),
# summary_stat = c("https://raw.githubusercontent.com/Broccolito/ggmugs_data/main/sumstat1.txt",
# "https://raw.githubusercontent.com/Broccolito/ggmugs_data/main/sumstat2.txt",
# "https://raw.githubusercontent.com/Broccolito/ggmugs_data/main/sumstat3.txt",
# "https://raw.githubusercontent.com/Broccolito/ggmugs_data/main/sumstat4.txt",
# "https://raw.githubusercontent.com/Broccolito/ggmugs_data/main/sumstat5.txt"),
# p1 = 1e-4,
# p2 = 1e-6,
# p3 = 1e-8,
# color1 = "#FFFFE0",
# color2 = "#FFC300",
# color3 = "#FF5733"
# )