LocalHelix - Your Personal DNA Analyzer

In a small village not so far away, all the Gauls shared their data with Roman companies... All except one! 💪 Meet LocalHelix, the brave software powered by privacy potion, keeping your DNA safe from the prying eyes of Rome’s data-mining legionaries. 🛡️ Unlike Cacofonix, it won’t share your secrets with anyone! 😉

This program analyzes your DNA to find interesting insights. Do not use for medical advice and always consult your doctor.

The main goal of this project is to get insights on our DNA without having to send our data to unknown companies.

How to run the program

Before anything, you need to download this project locally, either with Git or directly using the download button on the GitHub page.

With Docker

You can run the project with Docker. First, install Docker following the instructions on the official website. Then, you can optionally download the data folder provided on the release page of our GitHub project. You must place this folder in the localhelix folder (localhelix/data). Then run at the root of the project:

docker build --tag dna_analyzer .

and

docker run dna_analyzer

If everything went smoothly, you should see a URL appear in the log that looks like:

Running on http://172.17.0.3:5000

Open your browser and go to the mentioned URL (http://172.17.0.3:5000 here). On this page, you have to upload your DNA results (this website is on your machine, so your data is not sent to anybody). After clicking on the upload button, wait a few minutes and your results will appear!

With Python

To run the program, you need to have Python installed and a package installer like pip.

To install the dependencies, run the command (we recommend using a virtual environment):

pip install -r requirements.txt

Then, run the command:

python -m localhelix -i INPUT_FILE -o OUTPUT_FILE -d DATA_DIR

The input file is an SNP description file. The supported formats are 23andMe, Ancestry.com, and MyHeritage. To include more format, please open an issue and copy-paste the header of you file (until the names of the columns for a CSV/TSV).

The data directory will contain all the data required to generate your report. If an empty directory is provided, the program will download and preprocess the necessary documents. The process takes a lot of time. Otherwise, you can use an existing data directory. We provide such a directory on our GitHub. You can download it, unzip it, and link to it when you start your program.

The output file is a html file that you can open with your favorite web browser.

Data Sources

Currently, we include the following data sources:

• SNPedia
• ClinVar
• GWAS

When possible, we link our results to the original source. We strongly recommend to check it.

If you want us to include additional sources or information, please open an issue on our GitHub.

Support our work