Skip to main content

GWAS software that combines traditional statistical methods with the power of Artificial Intelligence

Project description

About GWAStic

GWAStic is a software for Genome-Wide Association Study (GWAS) that combines traditional statistical methods with the power of Artificial Intelligence (AI) for comprehensive genetic analysis.

Key Features:

  • Comprehensive Genetic Analysis: GWAStic offers a wide range of methods to analyze your genomic data, allowing you to explore the associations between genetic variants and traits of interest comprehensively.

  • AI-Enhanced Data Analysis: Harness the capabilities of machine learning and AI to uncover subtle patterns, interactions, and associations that may be missed by conventional statistical methods.

  • Genomic Prediction: Take your research to the next level by using GWAStic's advanced AI models for genomic prediction. Predict future health outcomes, disease risks, or phenotypic traits based on your genetic data and environmental factors.

  • User-Friendly Interface: GenoAI's intuitive interface makes it accessible to both novice and experienced researchers. Seamlessly navigate through your data, perform analyses, and visualize results with ease.

  • Customizable Workflows: Tailor your analysis to your specific research goals with customizable workflows. Define your parameters, select the appropriate statistical models, and integrate AI components as needed for a personalized analysis experience.

  • Collaborative Research: Collaborate seamlessly with colleagues and share your findings securely within the platform.

  • Frequent Updates: Stay at the forefront of genetic research with regular software updates. GWAStic incorporates the latest advancements in GWAS and AI methodologies to keep your analyses up-to-date.

Citation

Documentation

Installation

GWAStic software was build and successfully tested on Windows operating system (Windows 7 and 10).

->Install Anaconda (https://www.anaconda.com/distribution/)

conda create --name gwastic_env python=3.9

conda activate gwastic_env

conda install pip

pip install gwastic_desktop

Usage:

Contributions:

We are strongly looking for contributions.

References:

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

gwastic_desktop-0.1.4.tar.gz (45.9 MB view details)

Uploaded Source

Built Distribution

gwastic_desktop-0.1.4-py3-none-any.whl (59.5 MB view details)

Uploaded Python 3

File details

Details for the file gwastic_desktop-0.1.4.tar.gz.

File metadata

  • Download URL: gwastic_desktop-0.1.4.tar.gz
  • Upload date:
  • Size: 45.9 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.6.1 CPython/3.9.18 Windows/10

File hashes

Hashes for gwastic_desktop-0.1.4.tar.gz
Algorithm Hash digest
SHA256 06fd4e987fd77cca52966650fbe29008522a51939351864006a0913170896bbe
MD5 7def0617a93db4561ce6dffdf0956cd2
BLAKE2b-256 0b3be938886ddcbeabb1fcbb03d739082ab67ffa44a5aad02121deb5dec526b6

See more details on using hashes here.

File details

Details for the file gwastic_desktop-0.1.4-py3-none-any.whl.

File metadata

  • Download URL: gwastic_desktop-0.1.4-py3-none-any.whl
  • Upload date:
  • Size: 59.5 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.6.1 CPython/3.9.18 Windows/10

File hashes

Hashes for gwastic_desktop-0.1.4-py3-none-any.whl
Algorithm Hash digest
SHA256 bf443ef533f3c18e902567d2082cb02db61f6a3d2298a879939106f6c9d79e4d
MD5 fc4991febe1ccbe7a23049f7d866edf4
BLAKE2b-256 71a8ad03219240c059b63fc8804cd8921b9b53d83f7388d682b9a20aba3fc8cd

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page