Skip to main content

AlphaFold based Functional Impact Prediction of Missense Variations

Project description

AFFIPred: AlphaFold based Functional Impact Prediction of Missense Variations

Usage:

First, install the tool using pip.

pip install affipred

Provide input and output files with relative or absolute path:

affipred variants.vcf -o affipred_results.csv

The input should be a .vcf file while the output file name extension should be .csv.

The output file will contain all the features used to predict the impact of the variants alongside the AFFIPred scores and the prediction of functional impact of the variants.

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

affipred-0.1.2.1.tar.gz (4.1 kB view details)

Uploaded Source

File details

Details for the file affipred-0.1.2.1.tar.gz.

File metadata

  • Download URL: affipred-0.1.2.1.tar.gz
  • Upload date:
  • Size: 4.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.4.2 requests/2.22.0 setuptools/45.2.0 requests-toolbelt/0.8.0 tqdm/4.30.0 CPython/3.8.10

File hashes

Hashes for affipred-0.1.2.1.tar.gz
Algorithm Hash digest
SHA256 3af5af540467d4585edee2a1eff68d8d11f970d94a51240817f7170dc717259c
MD5 667c3232024bda3c98b3edd0da3c1519
BLAKE2b-256 99bd05bbcc3a0b116630afd03988bdc0954582c2fe5d36b19b6b2b0d3370a870

See more details on using hashes here.

Supported by

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