genome-tornado-plot-wrapper

Analyzing Copy Number Variation (CNV) Events within the PCAWG dataset via GenomeTornadoPlot

https://github.com/nicholas-abad/genome-tornado-plot-wrapper

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Repository

Analyzing Copy Number Variation (CNV) Events within the PCAWG dataset via GenomeTornadoPlot

Basic Info
  • Host: GitHub
  • Owner: nicholas-abad
  • Language: R
  • Default Branch: main
  • Homepage:
  • Size: 840 KB
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Created almost 2 years ago · Last pushed 11 months ago
Metadata Files
Readme Citation

README.md

GenomeTornadoPlot Wrapper

This is a Python wrapper for the GenomeTornadoPlot R script. It streamlines the process of running the GenomeTornadoPlot visualization on a batch of genes based on a provided CSV file.

Clone with Submodules

Make sure to clone this repository with the --recurse-submodules flag to include the necessary submodules:

bash git clone --recurse-submodules https://github.com/nicholas-abad/genome-tornado-plot-wrapper.git

If you've already cloned without submodules, run:

bash git submodule update --init --recursive

This will ensure that both GenomeTornadoPlot/ and GenomeTornadoPlot-files/ are available.

Using Conda

To ensure reproducibility and install all necessary dependencies (Python, R, and Bioconductor packages), you can use the provided environment.yml file.

Create and activate the environment:

If you're on Apple Silicon (M1/M2), run:

bash CONDA_SUBDIR=osx-64 conda env create -f environment.yml

Otherwise:

bash conda env create -f environment.yml

Then activate it:

bash conda activate gtp

This sets up the environment with all required packages for both Python and R scripts.

Repository Structure

genome-tornado-plot-wrapper/ ├── main.py # Main wrapper script ├── _singular_tornado_plot.R # R script wrapper ├── GenomeTornadoPlot/ # Git submodule ├── GenomeTornadoPlot-files/ # Git submodule └── README.md

Requirements

  • Python 3.x
  • pandas
  • R with required packages for GenomeTornadoPlot

Usage

To run the wrapper script:

bash python main.py \ --path-to-csv examples/sample_file.tsv \ --output-folder examples/output/ \ --delimiter "\t" \ --starting-index 0 \ --ending-index 3

Arguments

  • --path-to-csv: Path to the input CSV file.
  • --output-folder: Folder where output plots will be saved.
  • --delimiter: Delimiter used in the CSV file (e.g., ,, \t).
  • --starting-index: Start index of the CSV rows to process.
  • --ending-index: End index of the CSV rows to process.

Ensure the input CSV has at least #CHROM and GENE columns.

Examples

Running this main.py generates two PNG files: a chromosome-level plot and a zoomed-in version of that plot. An example of each of these can be seen below:

Chromosome-level Plot

Zoomed-in Plot

License

This wrapper script is based on the original GenomeTornadoPlot by chenhong-dkfz. Refer to their repository for licensing details.

Owner

  • Login: nicholas-abad
  • Kind: user
  • Location: Heidelberg, Germany

Machine Learning / Bioinformatics PhD Student at the DKFZ (German Cancer Research Institute)

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you'd like to cite GenomeTornadoPlot, please use the following citation. However, if you'd like to cite the results, please cite the paper."
authors:
  - family-names: Abad
    given-names: Nicholas
    orcid: https://orcid.org/0009-0004-8322-564X
title: "GenomeTornadoPlot Wrapper"
version: 1.0
identifiers:
  - type: doi
    value: https://www.biorxiv.org/content/10.1101/2024.06.03.597231v1
date-released: 2024-04-24

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