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Haplotype-resolved genomic structural variation detection with cuteHap

Project description

Logo

cuteHap is a haplotype-resolved structural variant (SV) detector designed for phased long-read sequencing data. It takes phased alignments generated by tools such as WhatsHap and LongPhase and detects haplotype-aware SVs in several minutes.

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Installation

We recommand the installation via conda or pip:

    $ conda install -c bioconda cutehap
    or
    $ pip install cutehap

Alternatively, installing from source with:

    $ git clone https://github.com/Meltpinkg/cuteHap.git
    $ cd cuteHap
    $ python setup.py install

Introduction

Structural variations (SVs), as a major category of genomic rearrangements, are capable of altering millions of nucleotides within the human genome. The detection of germline SVs and somatic mosaicism has emerged as a critical frontier in genomic research. Long-read sequencing technologies have demonstrated transformative potential in characterizing these variants. cuteHap is designed to produce high-quality, phased call sets for germline SV detection while simultaneously identifying low-frequency somatic mosaic events. The method delivers high-performance, haplotype-resolved SV detection and comprehensive detection of low-frequency mosaicism. A detailed usage guide documentation is available at here. A comprehensive demo and benchmarks are available at here.


Dependence

1. python3
2. scipy
2. pysam
3. Biopython
4. cigar
5. numpy
6. Cython

Quick Start

cuteHap <phased.bam> <reference.fa> <output.vcf> <workdir>

Changelog

cuteHap (v1.0.4)
1. update the logo and README.md
2. improve the mosaic mode

cuteHap (v1.0.3)
1. update the searching algorithm

cuteHap (v1.0.2)
1. modify the setup instructions
2. add installation via conda and pypi

cuteHap (v1.0.1)
1. update README.md
2. add user guide documentation
3. remove unused codes

cuteHap (v1.0.0)
1. the initial version of cuteHap

Contact

For advising, bug reporting and requiring help, please post on Github Issue or contact sqcao@stu.hit.edu.cn.

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