Skip to main content

Low-coverage structural variant (lcSV)

Project description

lcSV: low-coverage structural variant

Low-coverage Structural Variant (lcSV) is a Python package designed to infer structural variants (SVs) (deletions and duplications) from low-coverage whole-genome sequencing (lcWGS) data. Instead of relying on high-depth read or split-read evidence, lcSV leverages genome-wide coverage patterns to detect variations in copy number. LcSV operates as a population-based method: it iteratively proposes, refines, and selects haplotypes with varying haplotype frequencies, building a reservoir that represents the genetic diversity of a studying cohort. Using these inferred haplotypes and their estimated frequencies, lcSV subsequently assigns individual genotypes for each sample. Because this inference depends on shared haplotype information across individuals, lcSV is not suitable for single-sample analysis and should be run on a cohort level, ideally with large populations where allele frequency estimates are solid.

Installation

Please install lcSV with the following command:

pip install lcsv

Running lcSV

Please see the example jupyter notebook provided under examples.

Dependencies

LcSV supports Python 3.8+.

Installation requires numpy, pandas, matplotlib, statsmodels, and scipy.

Citation

LcSV is not yet a published work, so citing the GitHub repository suffices. Please refer to the CITATION.cff file.

Development

See the main site of lcSV: https://github.com/Suuuuuuuus/lcSV.

Bugs shall be submitted to the issue tracker. Please kindly provide a reproducible example demonstrating the problem.

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

lcsvpy-0.0.1.tar.gz (11.4 kB view details)

Uploaded Source

Built Distribution

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

lcsvpy-0.0.1-py3-none-any.whl (15.1 kB view details)

Uploaded Python 3

File details

Details for the file lcsvpy-0.0.1.tar.gz.

File metadata

  • Download URL: lcsvpy-0.0.1.tar.gz
  • Upload date:
  • Size: 11.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.8.15

File hashes

Hashes for lcsvpy-0.0.1.tar.gz
Algorithm Hash digest
SHA256 a8db4d41d10155425e777d2e2def67c98be61bccf1101bb8c0433f46f7304c49
MD5 b712f572cb4b64ade5f03d0cc109f497
BLAKE2b-256 1cc00bab0d40e7c87bc6b39458048783ad219e62128da4c85df723b55b15d8ef

See more details on using hashes here.

File details

Details for the file lcsvpy-0.0.1-py3-none-any.whl.

File metadata

  • Download URL: lcsvpy-0.0.1-py3-none-any.whl
  • Upload date:
  • Size: 15.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.8.15

File hashes

Hashes for lcsvpy-0.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 45fc6c6216c5e34bf8d62253f2a96d8a8a5f640c2d3bd8db727d4a7191a1436c
MD5 65c74146850acf4d85fe7c77f2154357
BLAKE2b-256 25a189358c863109360f4894fdae8cd852a7502594485938ed4d3d6071e78bde

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