🧬 gnomAD Python API

• 🧬 gnomAD Python API
  • #️⃣ What is gnomAD and the purpose of this script?
  • #️⃣ Update on the repository and gnomadR tool
  • #️⃣ Requirements and Installation
  • #️⃣ GUI | Usage
  • #️⃣ CLI | Usage & Options
  • #️⃣ CLI | Example Usages
  • #️⃣ Disclaimer
  • #️⃣ Contributing & Feedback
  • #️⃣ Developer
  • #️⃣ References

#️⃣ What is gnomAD and the purpose of this script?

gnomAD (The Genome Aggregation Database) [1] is aggregation of thousands of exomes and genomes human sequencing studies. Also, gnomAD consortium annotates the variants with allelic frequency in genomes and exomes.

Here, this API with both CLI and GUI versions is able to search the genes or transcripts of your interest and retrieve variant data from the database via gnomAD backend API that based on GraphQL query language.

#️⃣ Update on the repository and gnomadR tool

After the last update on the repository, gnomAD GraphQL API has been updated, and the query syntax and most of the keywords were deprecated or altered. Hence, the batch script is currently not able to retrieve the data from the gnomAD API and not able to generate outputs and plots.

If you are still looking forward a tool that automates fetching the data from gnomAD and you like R lang, you might check gnomadR!

gnomadR: Query gnomAD API from R by Dayne Filer (@daynefiler)

https://github.com/daynefiler/gnomadR

gnomadR package intends to provide an interface between R and the gnomAD API, powered by GraphQL. This package utilizes the qhql R package to send queries to gnomAD.

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#️⃣ Requirements and Installation

• Create a directory and download the "gnomad_api_cli.py" and "requirements.txt" files or clone the repository via Git using following command:

  git clone https://github.com/furkanmtorun/gnomad_python_api.git

• Install the required packages if you do not already:

  pip3 install -r requirements.txt

The requirements.txt contains required libraries for both GUI (graphical user interface) and CLI (command-line interface) versions.

• It's ready to use now!

If you did not install pip yet, please follow the instruction here.

#️⃣ GUI | Usage

In the GUI version of gnomAD Python API, Streamlit has been used.

Note: In GUI version, it is possible to generate plots from the data retrieved. This option is not available in CLI version since it is still under development.

So, it is recommended to use GUI version.

• To use GUI version of gnomAD Python API:

  streamlit run gnomad_api_gui.py

• Here are the screenshots for the GUI version:

  

  gnomAD Python API GUI - Main Screen

  

  gnomAD Python API GUI - Outputs

  

  gnomAD Python API GUI - Outputs and Plots

The outputs are also saved into outputs/ folder in the GUI version.

#️⃣ CLI | Usage & Options

Options	Description	Parameters
-filter_by	It defines the input type.	gene_name, gene_id, transcript_id, or rs_id
-search_by	It defines the input.	Type a gene/transcript identifier e.g.: TP53, ENSG00000169174, ENST00000544455 Type the name of file containig your inputs e.g: myGenes.txt
-dataset	It defines the dataset.	exac, gnomad_r2_1, gnomad_r3, gnomad_r2_1_controls, gnomad_r2_1_non_neuro, gnomad_r2_1_non_cancer, or gnomad_r2_1_non_topmed
-sv_dataset	It defines structural variants dataset.	gnomad_sv_r2_1, gnomad_sv_r2_1_controls, or gnomad_sv_r2_1_non_neuro
-reference_genome	It defines reference genome build.	GRCh37 or GRCh38
-h	It displays the parameters.	To get help via script: python gnomad_api_cli.py -h

❗ Here, for getting variants, gnomad_r2_1 and gnomad_sv_r2_1 are defined as default values for these two -dataset and -sv_dataset options, respectively.

❗ Also, you need to choose GRCh38 for retrieving variants from the gnomad_r3 dataset. However, in the GRCh38 build, structural variants are not available.

#️⃣ CLI | Example Usages

• How to list the variants by gene name or gene id?

  For gene name:

  python gnomad_api_cli.py -filter_by=gene_name -search_by="BRCA1" -dataset="gnomad_r2_1" -sv_dataset="gnomad_sv_r2_1"

  If you get data from gnomad_r3:

  python gnomad_api_cli.py -filter_by=gene_name -search_by="BRCA1" -dataset="gnomad_r3" -reference_genome="GRCh38"

  For Ensembl gene ID

  python gnomad_api_cli.py -filter_by=gene_id -search_by="ENSG00000169174" -dataset="gnomad_r2_1" -sv_dataset="gnomad_sv_r2_1"

• How to list the variants by transcript ID?

  python gnomad_api_cli.py -filter_by=transcript_id -search_by="ENST00000407236" -dataset="gnomad_r2_1"

• How to get variant info by RS ID (rsId)?

  python gnomad_api_cli.py -filter_by=rs_id -search_by="rs201857604" -dataset="gnomad_r2_1"

• How to list the variants using a file containing genes/transcripts?

  • Prepare your file that contains gene name, Ensembl gene IDs, Ensembl transcript IDs or RS IDs line-by-line.

    ENSG00000169174
    ENSG00000171862
    ENSG00000170445

  • Then, run the following command:

    python gnomad_api_cli.py -filter_by="gene_id" -search_by="myFavoriteGenes.txt" -dataset="gnomad_r2_1" -sv_dataset="gnomad_sv_r2_1"

  Please, use only one type of identifier in the file.

• Then, the variants will be listed in "outputs" folder in the folders according to their identifier (gene name, gene id, transcript id or rsId).

• That's all!

#️⃣ Disclaimer

All the outputs provided by this tool are for informational purposes only.

The information is not intended to replace any consultation, diagnosis, and/or medical treatment offered by physicians or healthcare providers.

The author of the app will not be liable for any direct, indirect, consequential, special, exemplary, or other damages arising therefrom.

#️⃣ Contributing & Feedback

I would be very happy to see any feedback or contributions to the project.

For problems and enhancement requests, please open an issue above.

⭐ If you like it, please do not forget give a star!

#️⃣ Developer

Furkan M. Torun (@furkanmtorun) | furkanmtorun@gmail.com | Academia: Google Scholar Profile

#️⃣ References

1. Karczewski, K.J., Francioli, L.C., Tiao, G. et al. The mutational constraint spectrum quantified from variation in 141,456 humans. Nature 581, 434–443 (2020). https://doi.org/10.1038/s41586-020-2308-7