HKU-BAL/ClairS

ClairS - a deep-learning method for long-read somatic small variant calling

/ 100

Emerging

This tool helps cancer researchers and clinical geneticists identify subtle genetic changes (somatic small variants) that occur in a tumor but not in healthy tissue. It takes raw DNA sequencing data from paired tumor and normal samples (specifically long-read data from Oxford Nanopore or PacBio, and also Illumina data) and outputs a list of these somatic variants, indicating what changed and where. This allows scientists to pinpoint mutations relevant to cancer development or treatment.

105 stars.

Use this if you need to accurately identify somatic small genetic variants (like SNVs and Indels) in paired tumor-normal samples using long-read sequencing data, especially for detecting low-frequency variants.

Not ideal if you are only working with a tumor sample without a paired normal sample for comparison, or if you are focused on germline (inherited) variants rather than somatic mutations.

cancer-genomics somatic-variant-calling long-read-sequencing tumor-normal-analysis bioinformatics

No Package No Dependents

Maintenance 10 / 25

Adoption 9 / 25

Maturity 16 / 25

Community 12 / 25

How are scores calculated?

Stars

105

Forks

Language

Python

License

BSD-3-Clause

Compare

ClairS and Clair3 ClairS and Clair3-RNA ClairS and ClairS-TO

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