Skip to main content

A package with utilities for training classifiers to recognize SVs in short read datasets

Project description

mlgenotype

This python package can be used to train machine learning models to genotype structural variants using aligned short read data. It was written by Nancy Fisher Hansen, a staff scientist in the Cancer Genetics and Comparative Genomics Branch (CGCG) of NHGRI, starting with code written by Gracelyn Hill and Jennifer C Lin. Nancy can be reached at nhansen@mail.nih.gov.

Software dependencies

  • pandas >= 1.0
  • scikit-learn >= 0.20

Clone the repository

git clone git://github.com/nhansen/mlgenotype

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

mlgenotype-0.1.9.tar.gz (10.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

mlgenotype-0.1.9-py3-none-any.whl (10.6 kB view details)

Uploaded Python 3

File details

Details for the file mlgenotype-0.1.9.tar.gz.

File metadata

  • Download URL: mlgenotype-0.1.9.tar.gz
  • Upload date:
  • Size: 10.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.7.12

File hashes

Hashes for mlgenotype-0.1.9.tar.gz
Algorithm Hash digest
SHA256 fd01e1112ce8ddc74d5ec47658b103236fa5156e8bef3648cd2219f3e410aa3c
MD5 b41df572829679e86e2e885c0329f34f
BLAKE2b-256 4ecd4235f6be93645c559f59903a9f146d720cc8b705e06c2099d2410a333172

See more details on using hashes here.

File details

Details for the file mlgenotype-0.1.9-py3-none-any.whl.

File metadata

  • Download URL: mlgenotype-0.1.9-py3-none-any.whl
  • Upload date:
  • Size: 10.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.7.12

File hashes

Hashes for mlgenotype-0.1.9-py3-none-any.whl
Algorithm Hash digest
SHA256 d696067fc7022809c0583a25d220608b21ad3762956dd85fefecea0d5d0eacca
MD5 d6785fa6bd5ef065983e86bb0fa15e82
BLAKE2b-256 4630acb45638263aa9912ad5be72b1aa9c67979fa937386d491e71e080583083

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