🐝 chromR is an R script designed for visualizing gene or domain positions on chromosomes or contigs. It allows users to customize their plots using keywords, file-based inputs, and color options, making it ideal for genomic data exploration.
- Plot genes, domains, or specific regions on chromosomes or contigs.
- Highlight specific genes, regions, or domains using keyword filtering (
--keywords). - Additional plot types:
--line_plot: display features as lines instead of points.--accumulated_plot: generate an accumulated gene count plot.
- Define colors for categories using R color names (e.g., "black") or hex codes (e.g., #1f77b4).
- Support for RColorBrewer palettes via --palette
- Accepts standard GFF (General Feature Format) files as input (
--gff_file). - Support for fill files (
--fill_file) in CSV/TSV (--formats). - Export processed data as tables in CSV or TSV formats (CSV/TSV with
--table)
- Strict mode (
--strict) to show only chromosomes containing keywords - High point support via layout file (
--layout) - Custom chromosome ordering (
--order_file) - Filter by number of chromosomes to display (
--number)
- 🚀 Command-Line Friendly. Run directly from the terminal or integrate into pipelines.
- 🖥️ RStudio Compatible. Easy to modify, debug, or execute within RStudio.
- Description: This graph shows the position of two transposons in
Saccharomyces cerevisiae R64, Ty1 (Ty1,gene) and TYA (TYA,gene) highlighted in green and orange. - Command used:
Rscript chromR.R -g ../genome/Saccharomyces_cerevisiae.R64-1-1.114.gff3 --keywords Ty1 gene TYA gene
- Genome example: Download Saccharomyces cerevisiae GFF
git clone https://github.com/mathiashole/chromR.git
cd chromR
Open R or RStudio and run:
install.packages(c("dplyr", "readr", "ggplot2"))
Ensure the following R packages are installed: dplyr, readr, ggplot2
- Navigate to the folder containing
chromR.Rand execute the script with the necessary arguments:
Rscript chromR.R --gff_file </path/to/file.gff> --keywords <keyword1> <keyword2> --colors <color1>
- Open chromR.R in RStudio.
- Set the arguments manually in the script or pass them interactively.
| Argument | Description | Example |
|---|---|---|
--gff_file / -g |
Path to the GFF file. | --gff_file data.gff |
--keywords / -k |
Keywords to highlight specific features. | --keywords gene1 CDS |
--colors / -c |
Colors for keywords (names or hex). | --colors black orange |
--palette / -p |
Select palette of RColorBrewer (names) | --palette Dark2 |
--layout / -l |
Optional layout input (e.g., ID file). | --layout data_ids.txt |
--accumulated_plot/ -ap |
Optional accumulated gene plot | --accumulated_plot |
--strict / -s |
Only show chromosomes that contain any of the keywords | --strict |
--line_plot / -lp |
Optional line plot gene. | --line_plot |
--order_file / -of |
File with custom chromosome order. | -of chrom_order.tsv |
--number / -n |
Maximum number of chromosomes to display. | -n 10 (Top 10 most longest) |
--fill_file / -ff |
File with regions to fill. | --fill_file regions.tsv |
--format / -f |
Fill and Order file format (csv/tsv) | --format tsv |
--table / -tab |
Export tables (csv/tsv). | --table csv |
💡 Note: Colors must match the number of keywords provided. They can be standard R color names or hex codes. In the case of hexadecimal colors, they must be put in quotes (e.g. "#F4A582").
Example 1: Basic Plot
Highlight gene1 and CDS in orange:
Rscript chromR.R --gff_file data.gff --keywords gene1 CDS --colors orange
Rscript chromR.R -g </path/of/file.gff> -k <keyword1> <keyword1_asociated> <keyword2> <keyword2_asociated>
If you have any genome data, put this data in TSV or CSV format and use GFF to map the chromosome.
Example 2: Fill data to Plot
Rscript chromR.R --gff_file data.gff --fill_file data_to_fill_information.tsv/.csv --format tsv/csv
Rscript chromR.R -g </path/of/file.gff> -ff <path/of/data_to_fill> -f <tsv/csv>
Example 1: Basic Plot
Highlight gene1 and CDS in orange:
args <- c("chromR.R", "--gff_file", "data.gff", "--keywords", "gene1 CDS", "--colors, "orange")
# Execution command
system2("Rscript", args = args)
If you have any genome data, put this data in TSV or CSV format and use GFF to map the chromosome.
Example 2: Fill data to Plot
args <- c("chromR.R", "--gff_file", "data.gff", "--fill_file", "data_to_fill_information.tsv/.csv", "--format", "tsv/csv")
# Execution command
system2("Rscript", args = args)
We welcome contributions!
Pull requests and 🌟 stars are always welcome.- For major changes, please open an issue first to discuss what you would like to change.
- Please make sure to update tests as appropriate.
See the full roadmap here
MIT © Mathias Mangino